prediction of toxicity, sensory responses and biological .../67531/metadc155623/m2/1/high_re… ·...

12

Prediction of Toxicity Sensory Responses and Biological Responses with the Abraham Model

William E Acree Jr1 Laura M Grubbs1 and Michael H Abraham2 1University of North Texas

2University College London 1United States

2United Kingdom

1 Introduction

Modern drug testing and design includes experimental in vivo and in vitro measurements

combined with in silico computations that enable prediction of the drug candidatersquos ADMET

(adsorption distribution metabolism elimination and toxicity) properties in the initial

stages of drug discovery Recent estimates place the discovery and development cost of a

small drug molecule close to US $13 billion from the time of conception to the time when

the drug finally reaches the market place Less than one-fourth of conceived drug candidates

proceed to clinical trial stage testing and of the compounds that enter clinical development

less than one-tenth actually receive government approval Reasons for the low success

percentage include poor efficacy low solubility unsatisfactory bioavailability unfavorable

pharmacokinetic properties toxicity concerns and drug-drug interactions degradation and

poor shelf-life stability Unfavorable pharmacokinetic and ADME properties toxicity and

adverse side effects account for up to two-thirds of drug failures Safety evaluation of drug candidates is crucial in the early stages of drug discovery and development For drug development safety requires that the potential drug molecule have sufficient selectivity for the desired target receptor so that an adequate dose range can be found where the intended pharmacological action is essentially the only physiological effect exhibited by the drug candidate Pharmaceutical compounds often exhibit the desired therapeutic action at one concentration range but may be quite toxic or even lethal at higher dosages and concentrations Drug induced liver injury (DILI) is the most frequent reason for discontinuation of new drug candidates Drug-induced liver injuries are classified as predictedintrinsic or idiosyncratic depending upon whether the injury is dose dependent Predictable DILIs are dose-dependent and the injury is largely reversible once the medication is discontinued Idiosyncratic DILIs on the other hand are independent of drug dosage level and believed to be related in part to individualrsquos hypersensitivity or immune system reactions to the medication Idiosyncratic DILIs depend upon the individualrsquos potential genetic and epigenetic constitution and immunological responses (Ozer et al 2010) Examples of drug andor drug candidates that either failed in late stage clinical testing or were removed from the market because of drug-induced liver injury concerns include ximelagatran (an anticoagulant that was promoted extensively as a replacement for

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Toxicity and Drug Testing 262

warfarin withdrawn in from US market in 2006) troglitazone (an anti-diabetic and anti-inflammatory drug withdrawn from the UK market in 1997 and US market in 2000) ebrotidine (an H2-reciptor antagonist marketed in Spain in 1997 withdrawn from the market in 1998) ticrynafen (a diuretic drug used in treatment of hypertension withdrawn from US market in 1979) benoxaprofen (a nonsteroidal anti-inflammatory drug withdrawn from US market in 1982) ibufenac (nonsteroidal anti-inflammatory drug used for the treatment of Rheumatoid arithritis withdrawn from UK market in 1970) and bromfenac (a nonsteroidal anti-inflammatory drug introduced in 1997 as a short-term analgesic for orthopedic pain withdrawn from the market in 1998) (Lamment et al 2008 Andrade et al 1999 Goldkind and Laine 2006) Other drugs such as valproic acid ketoconazole nicotinic acid rifampin chlorzoxazone isoniazid dantrolene nefazodone telethromycin nevirapine atomoxetine and inflixmab have received strong heptatoxicity warnings from the US Food and Drug Administration (Lamment et al 2008) Sibutramine and phenylpropanolamine used in the treatment of obesity were removed from the US market due to adverse effects associated with cardiovascular disease and hemorrhagic stroke respectively (Chaput and Tremblay 2010) Additional drugs withdrawn from the market for cardiovascular toxicities and concerns include rotecoxib (used to relieve acute pain and symptoms of chronic inflammation removed from market in 2005) and valdecoxib (used to relieve acute pain and symptoms of chronic inflammation removed from market in 2005) (Shi and Klotz 2008) Toxicity screening identifies drug candidates that exhibit predictableintrinsic drug-induced liver injury Idiosyncratic DILI occurs infrequently and only in treated patients which are highly susceptible to the given pharmaceutical compound Conventional preclinical safety testing is not the best method to detect idiosyncratic DILI Fourches and coworkers (2010) examined the possibility of using laboratory test animals as viable means to screen drug candidates for possible drug-induced liver injuries The authors compiled a data set of 951 compounds reported to induce a wide range of liver effects in humans and in different animal species Of the 951 compounds considered 650 had been identified as causing liver effects in humans 685 had been reported in the literature as causing liver effects in rodents and only 166 had shown liver effects in nonrodents The concordance between two species CONC(species A species) was defined as

( ) ( )

( )Toxic for both Aand B Nontoxic for both Aand B

CONC species A speciesBTotalnumber of compoundsstudied

(1)

as the number of compounds that exhibited toxicity for both animal species plus the number of compounds that showed notoxicity for both animal species divided by the total number of compounds considered Equation 1 was applied to the liver effect data gathered from the published literature The authors found a relatively low concordance of between 39 to 44 between different species ndash for human + rodents the concordance was equal to 442 ((402 + 18)951) and for human + nonrodents that concordance was equal to 399 ((122+257)951) Animal testing while informative does not necessarily provide an accurate indication of the pharmaceutical compoundrsquos likelihood to produce a liver effect in humans For the concordance calculations it was assumed that the pharmaceutical compound had been tested on all three species groups The above calculations further underscore the importance of finding suitable testing methods and models for use in drug discovery Drug safety considerations also include unwanted side effects and the impact that the pharmaceutical product will have on environment A significant fraction of the

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Prediction of Toxicity Sensory Responses and Biological Responses with the Abraham Model 263

pharmaceutically-active compounds sold each year find their way into the environment as the result of humananimal urine and feces excretion (excreted unchanged drugs or as drug metabolites) direct disposal of unused household drugs by flushing into sewage systems accidental spills and releases from manufacturing production sites and underground leakage from municipal sewage systems and infrastructures Dietrich and coworkers (2010) recently examined the environmental impact that four pharmaceutical compounds (carbamazepine diclofenac 17α-ethinylestradiol and metoprolol) had on the growth and reproduction of Daphnia Magna after exposure to the individual drugs and drug mixtures at environmentally relevant concentrations The authors found that effects were still detectable even several generations after first exposure to the pharmaceutical compound The Daphnia Magna had not developed complete resistance to the compound In the case of metoprolol both the body length of the females at first reproduction and the number of offspring per female were significantly less than the control group The same body length pattern was observed for females in the third and fourth generations No difference in female body length was observed in the first second and fifth generations The number of offspring per female was also reduced for the fourth generation Experimental data further revealed that drugs acting in combination can lead to impairments that are not predicted by the response to single substances alone The authors noted that aquatic organisms may not evolve a total resistance to pharmaceuticals in natural aquatic systems presumably due to high fitness costs One cannot exclude the potential long-term harmful effects that pharmaceuticals might have on the environment The Chapter will focus on the predicting the toxicity sensory response and biological response of organic and drug molecules using the Abraham solvation parameter model

2 Abraham solvation parameter model

The Abraham general solvation model is one of the more useful approaches for the analysis and prediction of the adsorption distribution and toxicological properties of potential drug candidates The method relies on two linear free energy relationships (lfers) one for transfer processes occurring within condensed phases (Abraham 1993ab Abraham et al 2004)

SP = c + e middot E + s middot S + a middot A + b middot B + v middot V (2)

and one for processes involving gas-to-condensed phase transfer

SP = c + e middot E + s middot S + a middot A + b middot B + l middot L (3)

The dependent variable SP is some property of a series of solutes in a fixed phase which in the present study will include the logarithm of drugrsquos water-to-organic solvent (log P) and blood-to-tissue partition coefficients the logarithm of the drugrsquos molar solubility in an organic solvent divided by its aqueous molar solubility (log CsoluteorgCsolutewater) the logarithm of the drugrsquos plasma-to-milk partition coefficient percent human intestinal absorption and the logarithm of the kinetic constant for human intestinal absorption and the logarithm of the human skin permeability coefficient (log kp) The independent variables or descriptors are solute properties as follows E and S refer to the excess molar refraction and dipolaritypolarizability descriptors of the solute respectively A and B are measures of the solute hydrogen-bond acidity and basicity V is the McGowan volume of the solute and L is the logarithm of the solute gas phase dimensionless Ostwald partition

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coefficient into hexadecane at 298 K For a number of partitions into solvents that contain large amounts of water at saturation an alternative hydrogen bond basicity parameter Bo is used for specific classes of solute alkylpyridines alkylanilines and sulfoxides Several of the published Abraham model equations for predicting the toxicity of organic compounds to different aquatic organisms use the Bo solute descriptor rather than the B descriptor Equations 1 and 2 contain the following three quantities (a) measured solute properties (b) calculated solute descriptors and (c) calculated equation coefficients Knowledge of any two quantities permits calculation of the third quantity through the solving of simultaneous equations and regression analysis Solute descriptors are calculated from measured partition coefficient (Psolutesystem) chromatographic retention factor (krsquo) and molar solubility (Csolutesolvent) data for the solutes dissolved in partitioning systems and in organic solvents having known equation coefficients Generally partition coefficient chromatographic retention factor and molar solubility measurements are fairly accurate and it is good practice to base the solute descriptor computations on observed values having minimal experimental uncertainty The computation is depicted graphically in Figure 1 by the unidirectional arrows that indicate the direction of the calculation using the known equation coefficients that connect the measured and solute descriptors Measured Psolutesystem and Csolutesolvent values yield solute descriptors The unidirectional red arrows originating from the center solute descriptor circle represent the equation coefficients that have been reported for nasal pungency aquatic toxicity upper respiratory irritation and inhalation anesthesia Abraham model correlations Plasma-to-milk partition ratio predictions are achieved (Abraham et al 2009a) through an artificial neural network with five inputs 14 nodes in the hidden layer and one node in the output layer Linear analysis of the plasma-to-milk partition ratios for 179 drugs and hydrophobic environmental pollutants revealed that drug molecules preferentially partition into the aqueous and protein phases of milk Hydrophobic environmental pollutants on the other hand partition into the fat phase

Fig 1 Outline illustrating the calculation of Abraham solute descriptors from experimental partition coefficient and solubility data and then using the calculated values to estimate sensory and biological responses such as toxicity of organic chemicals to aquatic organisms Draize eye scores convulsant activity of inhaled vapors upper respiratory irritation in mice and inhalation anesthesia in rats and mice

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Prediction of the fore-mentioned toxicities and sensory and biological responses does require a prior knowledge of the Abraham solute descriptors for the drug candidate of interest The descriptors E and V are quite easily obtained V can be calculated from atom and bond contributions as outlined previously (Abraham and McGowan 1987) The atom contributions are given in Table 1 note that the numerical values are in cm3 mol-1 A value of 656 cm3 mol-1 is subtracted for each bond in the molecule irrespective of whether the bond is a single double or triple bond For complicated molecules it is time consuming to count the number of bonds Bn but this can be calculated from the algorithm given by Abraham (1993a)

Bn = Nt ndash1 + R (4)

where Nt is the total number of atoms in the molecule and R is the number of rings

C 1635

N 1439

O 1243

Si 2683 P 2487 S 2291

Ge 3102 As 2942 Se 2781

Sn 3935 Sb 3774 Te 3614

Pb 4344 Bi 4219

H 871 He 676 B 1832

F 1048 Ne 851 Hg 3400

Cl 2095 Ar 1900

Br 2621 Kr 2460

I 3453 Xe 3290

Rn 3840

Table 1 Atom contributions to the McGowan volume in cm3 mol-1

Once V is available E can be obtained from the compound refractive index at 20oC If the compound is not liquid at room temperature or if the refractive index is not known the latter can be calculated using the freeware software of Advanced Chemistry Development (ACD) An Excel spreadsheet for the calculation of V and E from refractive index is available from the authors Since E is almost an additive property it can also be obtained by the summation of fragments either by hand or through a commercial software program (ADME Boxes 2010) The remaining four descriptors S A B and L can be determined by regression analysis of experimental water-to-organic solvent partition coefficient data chromatographic retention factor data and molar solubility data in accordance to Eqns 1 and 2 Solute descriptors are available for more than 4000 organic organometallic and inorganic solutes Large compilations are available in one published review article (Abraham et al 1993a) and in the supporting material that has accompanied several of our published papers (Abraham et al 2006 Abraham et al 2009b Mintz et al 2007) Experimental data-based solute descriptors have been obtained for a number of pharmaceutical compounds for example 230 compounds in an analysis of blood-brain distribution (Abraham et al 2006) Zissimos et al (2002a) calculated the S A and B solute descriptors of thirteen pharmaceutical compounds (propranolol tetracaine papaverine trytamine diclorfenac chloropromazine ibuprofen lidocaine deprenyl desipramine

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fluoxetine procaine and miconazole) from measured water-to-octanol water-to-chloroform water-to-cyclohexane and water-to-toluene partition coefficient data Equation coefficients for the four water-to-organic solvent partition coefficients were known Four mathematical methods based on the Microsoft Solver Progam the Triplex Program DescfitSIMPLEX minimization and Reverse Regression were investigated The authors (Zissimos et al 2002b) later illustrated the calculation methods using experimental data from seven high performance liquid chromatographic systems Solute descriptors of acetylsalicylic acid (Charlton et al 2003) naproxen (Daniels et al 2004a) ketoprofen (Daniels et al 2004b) and ibuprofen (Stovall et al 2005) have been calculated based on the measured solubilities of the respective drugs in water and in organic solvents Abraham model correlations for predicting blood-to-body organtissue partition

coefficients and the chemical toxicity of organic compounds towards aquatic organisms

involve chemical transfer between two condensed phases Predictive expressions for such

solute properties do not contain the Abraham model L solute descriptor There are however

published Abraham model correlations for estimating important sensory and biology

responses (such as convulsant activity of inhaled vapors upper respiratory irritation in

mice inhalation anesthesia in rats and in mice) that do involve solute transfer from the gas

phase To calculate the L solute descriptor one must convert water-to-organic solvent

partition coefficient data P into gas-to-organic solvent partition coefficients K

Log K = log P + log Kw (5)

and water-to-organic solvent solubility ratios CsoluteorganicCsolutewater into gas-to-organic

solvent solubility ratios CsoluteorganicCsolutegas

CsoluteorganicCsolutegas = CsoluteorganicCsolutewater CsolutewaterCsolutegas (6)

where CsolutewaterCsolutegas is the gas-to-water partition coefficient usually denoted as Kw

The water-to-organic solvent and gas-to-organic solvent partition coefficient equations are

combined in the solute descriptor computations If log Kw is not known it can be used as

another parameter to be determined This increases the number of unknowns from four (S

A B and L) to five (S A B L and Kw) but the number of equations is increased

significantly as well Numerical values of the four solute descriptors and Kw can be easily

calculated Microsoft Solver The computations are described in greater detail elsewhere

(Abraham et al 2004 Abraham et al 2010) The calculated value of the L descriptor can be

checked against an Abraham model correlation for estimating the L solute descriptor

L = ndash 0882 + 1183 E + 0839 S + 0454 A + 0157 B + 3505 V (7)

(N = 4785 SD = 031 R2 = 0992 F = 115279)

from known values of E S A B and V Van Noort et al (2010) cited a personnel

communication from Dr Abraham as the source of Eqn 7 If one is unable to locate

sufficient experimental data for performing the fore-mentioned regression analysis

commercial software (ADME Boxes version 2010) is available for estimating the molecular

solute descriptors from the structure of the compound Several correlations (Jover et al

2004 Zissimos et al 2002 Lamarche et al 2001 Platts et al 1999 Platts et al 2000) have

been reported for calculating the Abraham solute descriptors from the more structure-

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based topological-based andor quantum-based descriptors used in other QSAR and LFER

treatments

3 Presence and toxicity of pharmaceutical compounds in the environment

A significant fraction of the pharmaceutically-active compounds sold each year find their way into the environment as the result of humananimal urine and feces excretion (excreted unchanged drugs or as drug metabolites) direct disposal of unused household drugs by flushing into sewage systems accidental spills and releases from manufacturing production sites and underground leakage from municipal sewage systems and infrastructures While most pharmaceutical compounds are designed to target specific metabolic pathways in humans and domestic animals their action on non-target organisms may become detrimental even at very low concentrations The occurrence of pharmaceutical residues and metabolites in the environment is a significant public and scientific concern If not addressed pharmaceutical pollution will become even a bigger problem as the worldrsquos increasing and aging population purchases more prescription and more self-prescribed over-the-counter medicines to improve the quality of life There have been very few published studies that have attempted to estimate the quantity of each pharmaceutical compound that will be released each year into the environment Escher and coworkers (2011) evaluated the ecotoxicological potential of the 100 pharmaceutical compounds expected to occur in highest concentration in the wastewater effluent from both a general hospital and a psychiatric center in Switzerland The authors based the calculated drug concentrations on the hospitalrsquos records of the drugs administered in 2007 the number of patients admitted the days of hospital care and the water usage records for the main hospital wing that houses patients and here pharmaceuticals are excreted Amounts of the active drugs excreted unchanged in urine and feces were based on published excretion rates taken from the pharmaceutical literature Table 2 gives the usage pattern of 25 pharmaceutical compounds expressed as predicted effluent concentration in the hospital wastewater The predicted concentration is compared to compoundrsquos estimated baseline toxicity towards green algae (Pseudokirchneriella subcapitata) which was calculated from Eqn 8

ndashLog EC50 (Molar) = 095 log Dlipw(at pH = 7) + 153 (8)

using the drug moleculersquos water-to-lipid partition coefficient measured at an aqueous phase

pH of 7 The ldquobaselinerdquo concentration would be the concentration of the pharmaceutical

compound needed for the toxicity endpoint to be observed assuming a nonspecific narcosis

mechanism In the case of the green algae the toxicity endpoint corresponds to the molar

concentration of the tested drug substance at which the cell density biomass or O2

production is 50 of that of the untreated algae after a 72 to 96 hour exposure to the drug

The authors also reported predictive equations for estimating the baseline median lethal concentration for fish (Pimephales promelas 96-hr endpoint)

ndashLog LC50 (Molar) = 081 log Dlipw(at pH = 7) + 165 (9)

and the baseline effective concentration for mobility inhibition for water fleas (Daphnia magna 48-hr endpoint)


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Pharmaceutical Compound PECHWW (gL) PNECHWW (gL) PEC versus PNEC

Amiodarone 080 0009 PEC Greater

Clotrimazole 090 0014 PEC Greater

Trionavir 100 0028 PEC Greater

Progesterone 1585 140 PEC Greater

Meclozine 077 012 PEC Greater

Atorvastatin 099 016 PEC Greater

Isoflurane 94 298 PEC Greater

Tribenoside 079 026 PEC Greater

Ibuprofen 1140 660 PEC Greater

Clopidogrel 174 160 PEC Greater

Amoxicillin 499 625 PEC Smaller

Diclofenac 235 330 PEC Smaller

Floxacillin 389 233 PEC Smaller

Salicylic acid 172 134 PEC Smaller

Paracetamol 64 583 PEC Smaller

Thiopental 21 201 PEC Smaller

Oxazepam 184 32 PEC Smaller

Clarithromycin 541 122 PEC Smaller

Rifampicin 059 16 PEC Smaller

Tramadol 192 57 PEC Smaller

Carbazmazepine 050 18 PEC Smaller

Tetracaine 048 18 PEC Smaller

Metoclopramide 327 136 PEC Smaller

Prednisolone 210 139 PEC Smaller

Erythomycin 140 132 PEC Smaller

Table 2 Predicted Effluent Concentration of Pharmaceutical Compounds in the Wastewater of a General Hospital PECHWW (in gL) and the Predicted No Effect Concentration of the Pharmaceutical Compound to Green Algae PNECHWW (in gL)

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Ritonavir 086 003 PEC Greater


Diclofenac 730 331 PEC Greater

Mefanamic acid 538 078 PEC Greater

Lopinavir 026 005 PEC Greater

Nefinavir 071 016 PEC Greater


Clorprothixen 253 091 PEC Greater

Trimipramine 063 049 PEC Greater

Meclozin 011 012 PEC Smaller

Nevirapine 098 130 PEC Smaller

Venlafaxine 246 355 PEC Smaller

Promazine 167 270 PEC Smaller

Olanazpine 841 149 PEC Smaller

Levomepromazine 115 240 PEC Smaller

Clopidogrel 072 160 PEC Smaller

Methadone 375 105 PEC Smaller

Carbamazepine 500 177 PEC Smaller


Hexitidine 021 100 PEC Smaller

Duloxetine 038 230 PEC Smaller

Valproate 405 51 PEC Smaller

Fluoxetine 054 690 PEC Smaller

Lamotrigine 065 870 PEC Smaller

Clozapine 097 16 PEC Smaller

Diazepam 048 10 PEC Smaller


Pravastatin 339 77 PEC Smaller

Amoxacillin 228 625 PEC Smaller

Doxepin 017 490 PEC Smaller

Citolopram 051 17 PEC Smaller


Clomethiazole 028 23 PEC Smaller

Table 3 Predicted Effluent Concentration of Pharmaceutical Compounds in the Wastewater of a Psychiatric Hospital PECHWW (in gL) and the Predicted No Effect Concentration of the Pharmaceutical Compound to Green Algae PNECHWW (in gL)

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Most published baseline toxicity QSAR models were derived for neutral organic molecules and require the water-to-octanol partition coefficient Kow as the input parameter For compounds that can ionize the water-to-octanol partition coefficient is an unsuitable measure of bioaccumulation and chemical uptake into biomembranes the target site for baseline toxicants Of the 10 of 25 pharmaceutical compounds listed in Table 2 have a predicted effluent concentration greater predicted no effect value PNEC value These 10 compounds would be expected to exhibit toxicity towards the green algae if the algae where exposed to the hospital wastewater for 72 to 96 hours The drug concentrations in the hospital wastewater would be significantly reduced once the effluent entered the general sewer system Table 3 provides the predicted effluent concentration and calculated PNEC values of 33 pharmaceutical expected to be present in the wastewater from a psychiatric hospital The pharmaceutical concentrations were based on hospital records of the 2008 patients who received 70855 days of stationary care treatment Many of the individuals who received treatment had acute psychiatric disorders that required strong medication Nine of the 33 drugs listed have predicted effluent concentrations in excess of the PNEC value for green algae Readers are reminded that the ldquobaselinerdquo concentration assumes a nonspecific narcosis mechanism and that if the compound exhibits a reactive or other specific mode of toxic mechanism the concentration would be much less Since 1980 the US Food and Drug Administration has required that environmental risk assessments be conducted on pharmaceutical compounds intended for human and veterinary use before the product can be marketed Similar regulations were introduced by the European Union in 1997 The environmental impact tests are generally short-term studies that focus predominately on mortality as the toxicity endpoint for fish daphnids algae plants bacteria earthworms and select invertebrates (Khetan and Colins 2007) There have been very few experimental studies directed towards determining the no effect concentration (NEC) of pharmaceutical compounds and even fewer studies involving mixtures of pharmaceutical compounds The limited experimental data available shows that the NEC is highly dependent upon animal andor organism type and on the specific endpoint being considered For example the NEC for ibuprofen for 21 day growth for freshwater gastropod (Planorbis carinatus) is 102 mgL the NEC for 21 day reproduction for Daphnia magna is less than 123 mgL the NEC for 30 day survival of Japanese medaka (Oryzias latipes) is 01 mgL the NEC for 90 day survival of Japanese medaka is 01 gL Mortality due to ibuprofen exposure was found to increase as the medaka fish matured (Han et al 2010) More experimental NEC data is needed in order to properly perform environmental risk analyses Until such data becomes available one must rely on whatever acute toxicity data that one find and on in silico methods that allow one to predict missing experimental values from molecular structure considerations and from easy to measure physical properties

4 Abraham model Prediction of environmental toxicity of pharmaceutical compounds

Significant quantities of pharmaceutical drugs and personal healthcare products are discarded each year The discarded chemicals find their way into the environment and many end up in the natural waterways where they can have an adverse effect on marine life and other aquatic organisms Standard test methods and experimental protocols have been established for determining the median mortality lethal concentration LC50 for evaluating

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the chronic toxicity for determining decreased population growth and for quantifying developmental toxicity at various life stages for several different aquatic organisms Experimental determinations are often very expensive and time-consuming as several factors may need to be carefully controlled in order to adhere to the established recommended experimental protocol Aquatic toxicity data are available for relatively few organic organometallic and inorganic compounds To address this concern researchers have developed predictive methods as a means to estimate toxicities in the absence of experimental data Derived correlations have shown varying degrees of success in their ability to predict the aquatic toxicity of different chemical compounds In general predictive methods are much better at estimating the aquatic toxicities of compounds that act through noncovalent or nonspecific modes of action Nonpolar narcosis and polar narcosis are two such modes of nonspecific action Nonpolar narcotic toxicity is often referred to as ldquobaselinerdquo or minimum toxicity Polar narcotics exhibit effects similar to nonpolar narcotics however their observed toxicities are slightly more than ldquobaselinerdquo toxicity Most industrial organic compounds have either a nonpolar or polar narcotic mode of action which lacks covalent interactions between toxicant and organism Predictive methods are generally less successful in predicting the toxicity of compounds whose action mechanism involves electro(nucleo)philic covalent reactivity or receptor-mediated functional toxicity An example of a reactive toxicity mechanism would be alkane isothiocyanates that act as Michael-type acceptors and undergo N-hydro-C-mercapto addition to cellular thiol functional groups (Schultz et al 2008) The Abraham general solvation parameter model has proofed quite successful in predicting the toxicity of organic compounds to various aquatic organisms Hoover and coworkers (Hoover et al 2005) published Abraham model correlations for describing the nonspecific aquatic toxicity of organic compounds to Fathead minnow ndashlog LC50 (Molar 96 hr) = 0996 + 0418 E ndash 0182 S + 0417 A ndash 3574 B + 3377 V

(N= 196 SD = 0276 R2 = 0953 F = 7794) (11)

Guppy ndashlog LC50 (Molar 96 hr) = 0811 + 0782 E ndash 0230 S + 0341 A ndash 3050 B + 3250 V (N= 148 SD = 0280 R2 = 0946 F = 4931)

(12)

Bluegill ndashlog LC50 (Molar 96 hr) = 0903 + 0583 E ndash 0127 S + 1238 A ndash 3918 B + 3306 V (N= 66 SD = 0272 R2 = 0968 F = 3598)

(13)

Goldfish ndashlog LC50 (Molar 96 hr) = 0922 ndash 0653 E + 1872 S + ndash0329 A ndash 4516 B + 3078 V (N= 51 SD = 0277 R2 = 0966 F = 2537)

(14)

Golden orfe ndashlog LC50 (Molar 96 hr) = ndash0137 + 0931 E + 0379 S + 0951 A ndash 2392 B + 3244 V (N= 49 SD = 0269 R2 = 0935 F = 1270)

(15)

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and Medaka high-eyes ndashlog LC50 (Molar 96 hr) = ndash0176 + 1046 E + 0272 S + 0931 A ndash 2178 B + 3155 V (N= 44 SD = 0277 R2 = 0960 F = 1818)

(16)

ndashlog LC50 (Molar 48 hr) = 0834 + 1047 E ndash 0380 S + 0806 A ndash 2182 B + 2667 V (N= 50 SD = 0292 R2 = 0938 F = 1328)

(17)

The Abraham model described the median lethal toxicity (LC50) to within an average

standard deviation of SD = 0279 log units The derived correlations pertain to chemicals

that exhibit a narcosis mode-of-toxic action and can be used to estimate the baseline toxicity

of reactive compounds and to identify compounds whose mode-of-toxic action is something

other than nonpolar andor polar narcosis For example in the case of the fathead minnow

database Hoover et al (2005) noted that 13-dinitrobenzene 14-dinitrobenzene 2-

chlorophenol resorcinol catechol 2-methylimidazole pyridine 2-chloroaniline acrolein

and caffeine were outliers suggesting that their mode of action involved some type of

chemical specific toxicity These observations are in accord with the earlier observations of

Ramos et al (1998) and Gunatilleka and Poole (1999)

In a follow-up study (Hoover et al 2007) the authors reported Abraham model expressions for correlating the median effective concentration for immobility of organic compounds to three species of water fleas Daphnia magna ndashlog LC50 (Molar 24 hr) = 0915 + 0354 E + 0171 S + 0420 A ndash 3935 B + 3521 V (N= 107 SD = 0274 R2 = 0953 F = 4100)

(18)


(19)

Ceriodaphnia dubia ndashlog LC50 (Molar 24 hr amp 48 hr combined) = 2234 + 0373 E ndash 0040 S ndash 0437 A ndash - 3276 B + 2763 V (N= 44 SD = 0253 R2 = 0936 F = 1110)

(20)

Daphnia pulex ndashlog LC50 (Molar 24 hr amp 48 hr combined) = 0502 + 0396 E + 0309 S + 0542 A ndash - 3457 B + 3527 V (N= 45 SD = 0311 R2 = 0962 F = 2332)

(21)

The data sets used in deriving Eqns 18 ndash 21 included experimental log EC50 values for water flea immobility and for water flea death The two toxicity endpoints were taken to be equivalent Insufficient experimental details were given in many of the referenced papers for Hoover et al to decide whether the water fleas were truly dead or whether they were severely immobilized but still barely alive Often individual authors have reported the numerical value as a median immobilization effective concentration at the time of measurement and in a later paper the same authors referred to the same measured value as

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the median lethal molar concentration and vice versa Von der Ohe et al (2005) made similar observations regarding the published toxicity data for water fleas in their statement ldquo some studies use mortality (LC50) and immobilization (EC50 effective concentration 50) as identical endpoints in the context of daphnid toxicityrdquo Von der Ohe et al made no attempt to distinguish between the two For notational purposes we have denoted the experimental toxicity data for water fleas as ndashlog LC50 in the chapter We think that this notation is consistent with how research groups in most countries are interpreting the endpoint Organic compounds used in deriving the fore-mentioned water flea correlations were for the most common industrial organic solvents Hoover et al (2007) did find published toxicity data for six antibiotics to both Daphnia magna and Ceriodaphnia dubia (Isidori et al 2005) Solute descriptors are available for three of the six compounds One of the compounds ofloxacin has a carboxylic acid functional group and would not be expected to fall on the toxicity correlation for nonpolarndashpolar narcotic compounds to daphnids Solute descriptors for the remaining two compounds erythromycin (E = 197 S = 355 A = 102 B = 471 and V = 577) and clarithromycin (E = 272 S = 365 A = 100 B = 498 and V = 5914) differ considerably from the the compounds used in deriving Eqns 18-21 There was no obvious structural reason for the authors to exclude erythromycin and clarithromycin from the database however except that they did not want the calculated equation coefficients to be influenced by two compounds so much larger than the other compounds in the database and the calculated solute descriptors for both antibiotics were based on very limited number of experimental observations Inclusion of erythromycin (ndashlog LC50 = 451 for Daphnia magna and ndashlog LC50 = 486 for Ceriodaphnia dubia) and clarithromycin (ndashlogLC50 = 460 for Ceriodaphnia dubia and ndashlog LC50 = 446 for Daphnia magna) in the regression analyses yielded Daphnia magna ndashlog LC50 (Molar 24 hr) = 0896 + 0597 E ndash 0089 S + 0462 A ndash 3757 B + 3460 V (22)

Ceriodaphnia dubia ndashlog LC50 (Molar 24 hr) = 1983 + 0373 E + 0077 S ndash 0576 A ndash 3076 B + 2918 V (23)

Both correlations are quite good The one additional compound had little effect on the statistics SD = 0253 (data set B correlation in Hoover et al 2007) versus SD = 0253 for Daphnia magna and SD = 0256 versus SD = 0253 for Ceriodaphnia dubia Abraham model correlations have also been developed for estimating the baseline toxicity of organic compounds to Tetrahymena pyriformis (Hoover et al 2007) Spirostomum ambiguum (Hoover et

al 2007) Psuedomonas putida (Hoover et al 2007) Vibrio fischeri (Gunatilleka and Poole 1999) and several tadpole species (Bowen et al 2006)

5 Methods to remove pharmaceutical products from the environment

The fate and effect of pharmaceutical drugs and healthcare products is not easy to predict

Medical compounds may be for human consumption to combat diseases or treat illnesses or

to relive pain and reduce inflammation Many anti-inflammatory and analgesic drugs are

available commercially without prescription as over-the-counter medications with an

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estimated annual consumption of several hundred tons in developed countries

Pharmaceutical products are also used as veterinary medicines to treat illnesses to promote

livestock growth to increase milk production to manage reproduction and to prevent the

outbreak of diseases or parasites in densely populated fish farms Antibiotics and

antimicrobials are used to control and prevent diseases caused by microorganisms

Antiparasitic and anthelmintic drugs are approved for the treatment and control of internal

and external parasites The pharmaceutical compounds find their way into the environment by

many exposure pathways humananimal urine and feces excretion discharge and runoff

from fish farms as shown in Figure 2 Once in the environment the drugs and their

degradation metabolites are adsorbed onto the soil and dissolved into the natural waterways

Fig 2 Environmental occurrence and fate of pharmaceutical compounds used in human treatments and veterinary applications

Published studies have reported the environmental damage that human and veterinary compounds have on aquatic organisms and microorganisms on birds and on other forms of wildlife For example diclofenac (drug commonly used in ambulatory care) inhibits the microorganisms that comprise lotic river biofilms at a drug concentration level around 100 gL (Paje et al 2002) and damages the kidney and liver cell functions of rainbow trout at concentration levels of 1 gL (Triebskorn et al 2004) Diclofenac affects nonaquatic organisms as well India Pakisan and Nepal banned the manufacture of veterinary formulations of diclofenac to halt the decline of three vulture species that were being poisoned by the diclofenac residues present in domestic livestock carcasses (Taggart et al 2009) The birds died from kidney failure after eating the diclofenac-tained carcasses Concerns have also been expressed about the safety of ketoprofen Naidoo and coworkers (2010ab) reported vulture mortalities at ketoprofen dosages of 15 and 5 mgkg vulture body weight which is within the level for cattle treatment Residues of two fluorquinolone veterinary compounds (enrofloxacin and ciprofloxacin) found in unhatched eggs of giffon

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vultures (Gyps fulvus) and red kites (Milvus milvus) are thought to be responsible for the observed severe alterations of embryo cartilage and bones that prevented normal embryo development and successful egg hatching (Lemus et al 2009) Removal of pharmaceutical residues and metabolites in municipal wastewater treatment facilities is a major challenge in reducing the discharge of these chemicals into the environment Many wastewater facilities use an ldquoactivated sludge processrdquo that involves treating the wastewater with air and a biological floc composed of bacteria and protozoans to reduce the organic content Treatment efficiency for removal of analgesic and anti-inflammatory drugs varies from ldquovery poorrdquo to ldquocomplete breakdownrdquo (Kulik et al 2008) and depends on seasonal conditions pH hydraulic retention time and sludge age (Tauxe-Wuersch et al 2005 Nikolaou et al 2005) Advanced treatment processes in combination with the activated sludge process results in greater pharmaceutical compound removal from wastewater Advanced processes that have been applied to the effluent from the activated sludge treatment include sand filtration ozonation UV irridation and activated carbon adsorption Of the fore-mentioned processes ozonation was found to be the most effective for complete removal for most analgesic and anti-inflammatory drugs Ozone reactivity depends of the functional groups present in the drug molecule as well as the reaction conditions For example the presence of a carboxylic functional group on an aromatic ring reduces ozone reaction with the aromatic ring carbons Carboxylic groups are electron withdrawing Electron-donating substituents such as ndashOH groups facilitate the attack of ozone to aromatic rings Not all pharmaceutical compounds are reactive with ozone For such compounds it may be advantageous to perform the ozonation under alkaline conditions where hydroxyl radicals are readily abundant Hydroxyl radicals are highly reactive with a wide range of organic compounds converting the compound to simplier and less harmful intermediates With sufficient reaction time and appropriate reaction conditions hydroxyl radicals can convert organic carbon to CO2 Several methods have been successfully employed to generate hydroxyl radicals Fenton oxidation is an effective treatment for removal of pharmaceutical compounds and other organic contaminants from wastewater samples The process is based on

Fe2+ + H2O2 ------gt Fe3+ + OHndash + OH (24)

the production of hydroxyl radicals from Fentonrsquos reagent (Fe2+H2O2) under acidic conditions with Fe2+ acting as a homogeneous catalyst Once formed hydroxyl radicals can oxidize organic matter (ie organic pollutants) with kinetic constants in the 107 to 1010 Mndash1 sndash1 at 20 oC (Edwards et al 1992 Huang et al 1993) Fentonrsquos technique has been used both as a wastewater pretreatment prior to the activated sludge process and as a post-treatment method after the activated sludge process A full-scale pharmaceutical wastewater treatment facility using the Fenton process as the primary treatment method followed by a sequence of activated sludge processes as the secondary treatment method has been reported to provide an overall chemical oxygen demand removal efficiency of up to 98 (Tekin et al 2006) UVH2O2 is an effective treatment for removal of pharmaceutical compounds and other organic contaminants from wastewater samples The effluent is subjected to UV radiation Some of the dissolved organic will absorb UV light directly resulting in the destruction of chemical bonds and subsequent breakdown of the organic compound Hydrogen peroxide is added to treat those compounds that do not degrade quickly or efficiently by direct UV photolysis Hydrogen peroxide undergoes photolytic cleavage to OH radicals

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H2O2 + h ------gt 2 OH (25)

at a stoichiometric ratio of 12 provided that the radiation source has sufficient emission at 190 ndash 200 nm Disadvantages of the advanced oxidation processes are the high operating costs that are associated with (a) high electricity demand (ozone and UVH2O2) (b) the relatively large quantities of oxidants andor catalysts consumed (ozone hydrogen peroxide and iron salts) and (c) maintaining the required pH range (Fenton process)

Fig 3 Basic photocatalyic process involving TiO2 particle

Photo-catalytic processes involving TiO2 andor TiO2 nanoparticles have also been successful in removing pharmaceutical compounds pharmaceutical compounds (PC) from aqueous solutions The basic process of photocatalysis consists of ejecting an electron from the valence band (VB) to the conduction band (CB) of the TiO2 semiconductor

TiO2 + h rarr ecbminus + hvb+ (26)

creating an h+ hole in the valence band This is due to UV irradiation of TiO2 particles with an energy equal to or greater than the band gap (h gt 32 eV) The electron and hole may recombine or may result in the formation of extremely reactive species (like OH and O2minus) at the semi-conductor surface

hvb+ + H2O rarr OH + H+ (27)

hvb+ + OHminus rarr OHads (28)

ecbminus + O2 rarr O2minus (29)

as depicted in Figure 3 andor a direct oxidation of the dissolved pharmaceutical compound (PC)

hvb+ + PCads rarr PC+ads (30)

The O2minus that is produced in reaction scheme 35 undergoes further reactions to form

O2minus + H+ rarr HO2 (31)

H+ + O2minus + HO2 rarr H2O2 + O2 (32)

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H2O2 + h rarr 2 OH (33)

additional hydroxyl radicals that subsequently react with the dissolved pharmaceutical compounds (Gad-Allah et al 2011) Titanium dioxide is used in the photo-catalytic processes because of its commercial availability and low cost relatively high photo-catalytic activity chemical stability resistance to photocorrosion low toxicity and favorable wide band-gap energy Published studies have shown that sonochemical degradation of pharmaceutical and pesticide compounds can be effective for environmental remediation Sonolytic degradation of pollutants occurs as a result of the continuous formation and collapse of cavitation bubbles on a microsecond time scale Bubble collapse leads to the formation of a hot nucleus characterized with extremely high temperatures (thousands of degrees) and pressure (hundreds of atmospheres)

6 Abraham model Prediction of sensory and biological responses

Drug delivery to the target is an important consideration in drug discovery The drug must

reach the target site in order for the desired therapeutic effect to be achieved Inhaled

aerosols offer significant potential for non-invasive systemic administration of therapeutics

but also for direct drug delivery into the diseased lung Drugs for pulmonary inhalation are

typically formulated as solutions suspensions or dry powders Aqueous solutions of drugs

are common for inhalational therapy (Patton and Byron 2007) Yet about 40 of new active

substances exhibit low solubility in water and many fail to become marketed products due

to formulation problems related to their high lipophilicity (Tang et al 2008 Gursoy and

Benita 2004) Formulations for drug delivery to the respiratory system include a wide

variety of excipients to assist aerosolisation solubilise the drug support drug stability

prevent bacterial contamination or act as a solvent (Shaw 1999 Forbes et al 2000) Organic

solvents that are used or have been suggested as propellents for inhalation drug delivery

systems include semifluorinated alkanes (Tsagogiorgas et al 2010) binary ethanol-

hydrofluoroalkane mixtures (Hoye and Myrdal 2008) fluorotrichloromethane

dichlorodifluoromethane and 12-dichloro-1122-tetrafluoroethane (Smyth 2003)

Eye irritation thresholds (EIT) nasal irritation (pungency) thresholds (NPT) and odor detection thresholds (ODT) are related in that together they provide a warning system for unpleasant noxious and dangerous chemicals or mixtures of chemicals ODT values should not be confused with odor recognition The latter area of research was revolutionized by the discovery of the role of odor receptors by Buck and Axel (Nobel Prize in physiology and medicine 2004) It is now known that there are some 400 different active odor receptors in humans that a given odor receptor can interact with a number of different chemicals and that a given chemical can interact with several different odor receptors (Veithen et al 2009 Veithen et al 2010) This leads to an almost infinite matrix of interactions and is a major reason why any connection between molecular structure and odor recognition is limited to rather small groups of chemicals (Sell 2006) However the first indication of an odor is given by the detection threshold only at appreciably higher concentrations of the odorant can it be recognized Another vital difference between odor detection and odor recognition is that ODT values can be put on a rigorous quantitative scale (Cometto-Muňiz 2001) whereas odor recognition is qualitative and subject to leaning and memory (Wilson and Stevenson 2006) As we shall see it is possible with some limitations to obtain equations

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that connect ODT values with chemical structure in a way that is impossible for odor recognition A lsquoback-uprsquo warning system is provided through nasal irritation (pungency) thresholds where NPT values are about 103 larger than ODT Nasal pungency occurs through activation of the trigeminal nerve and so has a different origin to odor itself Because chemicals that illicit nasal irritation will generally also provoke a response with regard to odor detection it is not easy to determine NPT values without interference from odor Cometto-Muňiz and Cain used subjects with no sense of smell anosmics in order to obtain NPT values through a rigorous systematic method a detailed review is available (Cometto-Muňiz et al 2010) Cometto-Muňiz and Cain also devised a similar rigorous systematic method to obtain eye irritation thresholds (Cometto-Muňiz 2001) Values of EIT are very close to NPT values Eye irritation and nasal irritation (or pungency) are together known as sensory irritation In addition to these human studies a great deal of work has been carried out on upper respiratory tract irritation in mice A quantitative scale was devised by Alarie (Alarie 1966 1973 1981 1988) and developed into a procedure for establishing acceptable exposure limits to airborne chemicals Before applying any particular equation to biological activity of VOCs it is useful to consider various possible models (Abraham et al 1994) A number of models were examined the lsquotwo-stagersquo model shown in Figure 4 gave a good fit to experimental data whilst still allowing for unusual or lsquooutlyingrsquo effects In stage 1 the VOC is transferred from the gas phase to a receptor phase This transfer will resemble the transfer of chemicals from the gas phase to solvents that have similar chemical properties to the receptor phase In particular there will be lsquoselectivityrsquo between VOCs in accordance with their chemical properties and the chemical properties of the receptor phase In stage 2 the VOC activates the receptor If this is simply an on-off process so that all VOCs activate the receptor similarly then the resultant biological activity will correspond to the selectivity of the VOCs in the first stage and can then be represented by some structure-activity correlation However if some of the VOCs activate the receptor through lsquospecificrsquo effects they will appear as outliers to any structure-property correlation Indeed if the majority of VOCs act through specific effects then no reasonable structure-activity correlation will be obtained

Gas phase

Receptor phase

R1

2

VOC

Fig 4 A two-stage mechanism for the biological activity of gases and vapors R denotes the receptor

A stratagem for the analysis of biological activity of VOCs in a given process is therefore to

construct some quantitative structure-activity equation that resembles similar equations for

the transfer of VOCs from the gas phase to solvents If the obtained equation is statistically

and chemically reasonable then it may be deduced that stage 1 is the main step If a

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reasonable equation is obtained but with a number of outliers then stage 1 is probably the

main step for most VOCs but stage 2 is important for the VOCs that are outliers If no QSAR

can be set up then stage 2 will be the main step for most VOCs The linear free energy

relationship or LFER Eqn 3 has been applied to transfers of compounds from the gas phase

to a very large number of solvents (Abraham et al 2010a) and so is well suited as a general

equation for the analysis of biological activity of VOCs Early work on attempts to correlate ODT values with various VOC properties has been summarized (Abraham 1996) The first general application of Eqn 3 to ODT values yielded Eqn 34 (Abraham et al 2001 2002) Note that (1ODT) is used so that as log (1ODT) becomes larger the VOC becomes more potent and that the units of ODT are ppm There were a considerable number of outliers including carboxylic acids aldehydes propanone octan-1-ol methyl acetate and t-butyl alcohol suggesting that for many of the VOCs studied stage 2 in Figure 4 is important Log (1ODT) = -5154 + 0533 middot E + 1912 middot S + 1276 middot A + 1559 middot B + 0699 middotL

(N= 50 SD = 0579 R2 = 0773 F = 287) (34)

Aldehydes and carboxylic acids could be included in the correlation through an indicator variable H that takes the value H = 20 for aldehydes and carboxylic acids and H = 0 for all other VOCs The correlation could also be improved slightly by use of a parabolic expression in L leading to Eqn 35 (Abraham et al 2001 2002) Log (1ODT) = -7720 - 0060 middot E + 2080 middot S + 2829 middot A + 1139 middot B + +2028 middot L - 0148 middot L2 + 1000middot H (N= 60 SD = 0598 R2 = 0850 F = 440)

(35)

Although Eqn 35 is more general than Eqn 34 it suffers in that it cannot be compared to equations for other processes obtained through the standard Eqn 3 Coefficients for equations that correlate the transfer of compounds from the gas phase to solvents as log K the gas-solvent partition coefficient are given in Table 4 (Abraham et al 2010a) The most important coefficients are the s-coefficient that refers to the solvent dipolarity the a-coefficient that refers to the solvent hydrogen bond basicity the b-coefficient that refers to the solvent hydrogen bond basicity and the l-coefficient that is a measure of the solvent hydrophobicity For a solvent to be a model for stage 1 in the two-stage mechanism we expect it to exhibit both hydrogen bond acidity and hydrogen bond basicity since the peptide components of a receptor will include the ndashCO-NH- entity In Table 4 we give details of solvents mainly with significant b- and a-coefficients There is only a rather poor connection between the coefficients in Eqn 42 and those for the secondary amide solvents in Table 4 suggesting once again that for odor thresholds stage 2 must be quite important The importance of stage 2 is illustrated by the observations of a lsquocut-offrsquo effect in odor detection thresholds (Cometto-Muňiz and Abraham 2009a 2009b 2010a 2010b) On ascending a homologous series of chemicals ODT values decrease regularly with increase in the number of carbon atoms in the compounds That is the chemicals become more potent However a point is reached at which there is no further decrease in ODT or even ODTs begin to rebound and increase with increase in carbon chain length (Cometto-Muňiz and Abraham 2009a 2010a) This outcome could possibly be due to a size effect A point is reached at which the VOC becomes too large and the increase in potency reflected in decreasing ODTs is halted as just described

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Solvent c E s a b l

Methanol -0039 -0338 1317 3826 1396 0773

Ethanol 0017 -0232 0867 3894 1192 0846

Propan-1-ol -0042 -0246 0749 3888 1076 0874

Butan-1-ol -0004 -0285 0768 3705 0879 0890

Pentan-1-ol -0002 -0161 0535 3778 0960 0900

Hexan-1-ol -0014 -0205 0583 3621 0891 0913

Heptan-1-ol -0056 -0216 0554 3596 0803 0933

Octan-1-ol -0147 -0214 0561 3507 0749 0943

Octan-1-ol (wet) -0198 0002 0709 3519 1429 0858

Ethylene glycol -0887 0132 1657 4457 2355 0565

Water -1271 0822 2743 3904 4814 -0213

N-Methylformamide -0249 -0142 1661 4147 0817 0739

N-Ethylformamide -0220 -0302 1743 4498 0480 0824

N-Methylacetamide -0197 -0175 1608 4867 0375 0837

N-Ethylacetamide -0018 -0157 1352 4588 0357 0824

Formamide -0800 0310 2292 4130 1933 0442

Diethylether 0288 -0347 0775 2985 0000 0973

Ethyl acetate 0182 -0352 1316 2891 0000 0916

Propanone 0127 -0387 1733 3060 0000 0866

Dimethylformamide -0391 -0869 2107 3774 0000 1011

N-Formylmorpholine -0437 0024 2631 4318 0000 0712

DMSO -0556 -0223 2903 5037 0000 0719

Table 4 Coefficients in Eqn 3 for Partition of Compounds from the Gas Phase to dry Solvents at 298 K

As regards nasal pungency thresholds a very detailed review is available on the anatomy and physiology of the human upper respiratory tract the methods that have been used to assess irritation and the early work on attempts to devise equations that could correlate nasal pungency thresholds (Doty et al 2004) The first application of Eqn 3 to nasal pungency thresholds used a variety of chemicals including aldehydes and carboxylic acids (Abraham et al 1998c) Later on NPT values for several terpenes were included (Abraham et al 2001) to yield Eqn 36 (Abraham et al 2010b) with NPT in ppm of all the chemicals tested only acetic acid was an outlier Note that the term smiddot S was statistically not significant and was excluded Unlike ODT it seems as though for the compounds studied stage 1 in

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the two-stage mechanism is the only important step This is reflected in that there are several solvents in Table 4 with coefficients quite close to those in Eqn 36 N-methylformamide is one such solvent and would be a reasonable model for solubility in a matrix containing a secondary peptide entity Log (1NPT) = -7700 + 1543 middot S + 3296 middot A + 0876 middot B + 0816 middot L

(N = 47 SD = 0312 R2 = 0901 F = 450) (36)

Along a homologous series of VOCs the only descriptor in Eqn 36 that changes significantly is L Since L increases regularly along a homologous series then log 1(1NPT) will increase regularly ndash that is the VOC will become more potent A very important finding (Cometto-Muňiz et al 2005a) is that this regular increase does not continue indefinitely For example along the series of alkyl acetates log (1NPT) increases up to octyl acetate but decyl acetate cannot be detected This is not due to decyl acetate having too low a vapor pressure to be detected but is a biological lsquocut-offrsquo effect One possibility (Cometto-Muňiz et

al 2005a) is that for homologous series the cut-off point is reached when the VOC is too large to activate the receptor The effect of the cut-off point is shown in Figure 5 where log (1NPT) is plotted against the number of carbon atoms in the n-alkyl group for n-alkyl acetates A similar situation is obtained for the series of carboxylic acids where the irritation potency increases as far as octanoic acid which now exhibits the cut-off effect However the compounds phenethyl alcohol vanillin and coumarin also failed to provoke nasal irritation which suggests that stage 1 in the two-stage process is not always the limiting step Two other equations for NPT have been reported (Famini et al 2002 Luan et al 2010) but the equations contain fewer compounds than Eqn 36 and neither of them have improved statistics

Fig 5 A plot of log (1NPT) for n-alkyl acetates against N the number of carbon atoms in the n-alkyl group observed values calculated values from Eqn 36

A related property to eye irritation in humans is the Draize rabbit eye irritation test (Draize et al 1944) A given substance is applied to the eye of a living rabbit and the effects of the substance on various parts of the eye are graded and used to derive an eye irritation score

N

Lo

g (

1N

PT

)

1086420

-1

-2

-3

-4

-5

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All kinds of substances have been applied including soaps detergents aqueous solutions of acids and bases and various solids The test is so distressing to the animal that it has largely been phased out but Draize scores of chemicals as the pure liquid are of value and were used to develop a quantitative structure-activity relationship (Abraham et al 1998a) It was reasoned that if Draize scores of the pure liquids DES were mainly due to a transport mechanism for example step 1 in Figure 4 then they could be converted into an effect for the corresponding vapors through DES Po = K Here K is a gas to solvent phase equilibrium or partition coefficient Po is the saturated vapor pressure of the pure liquid in ppm at 298 K and DES Po is equivalent to the solubility of a gaseous VOC in the appropriate receptor phase Values of DES for 38 liquids were converted into DES Po and the latter regressed against the Abraham descriptors The point for propylene carbonate was excluded and for the remaining 37 compounds Eqn 37 was obtained the term in emiddot E was not significant and was excluded The coefficients in Eqn 37 quite resemble those for solubility in N-methylformamide Table 4 and this suggests that the assumption of a mainly transport mechanism is reasonable

Log (DES Po) = -6955 + 1046 middot S + 4437 middot A + 1350 middot B + 0754 middot L

(N = 37 SD = 0320 R2 = 0951 F = 1559) (37)

At that time values of EIT for only 17 compounds were available and so an attempt was made to combine the modified Draize scores with EIT values in order to obtain an equation that could be used to predict EIT values in humans (Abraham et al1998b) It was found that a small adjustment to DES Po values by 066 was needed in order to combine the two sets of data as in Eqn 38 SP is either (DES Po - 066 or EIT) EIT is in units of ppm Log (SP) = -7943 + 1017 middot S + 3685 middot A + 1713 middot B + 0838 middot L

(N = 54 SD = 0338 R2 = 0924 F = 14969) (38)

A slightly different procedure was later used to combine DES Po values for 68 compounds and 23 EIT values (the nomenclature MMAS was used instead of DES) For all 91 compounds Eqn 39 was obtained Instead of the adjustment of -066 to DES Po an indicator variable I was used this takes the value I = 0 for the EIT compounds and I = 1 for the Draize compounds (Abraham et al 2003) Log (SP) = -7892 - 0397 middot E + 1827 middot S + 3776 middot A + 1169 middot B + 0785 middot L + 0568 middot I

(N = 91 SD = 0433 R2 = 0936 F = 2045) (39)

The eye irritation thresholds in humans based on a standardized systematic protocol were those determined over a number of years (Cometto-Muňiz amp Cain 1991 1995 1998 Cometto-Muňiz et al 1997 1998a 1998b) Later work (Cometto-Muňiz et al 2005b 2006 2007a 2007b Cometto-Muňiz and Abraham 2008) revealed the existence of a cut-off point in EIT on ascending a number of homologous series Just as with NPT these cut-off points are not due to the low vapor pressure of higher members of the homologous series but appear to relate to a lack of activation of the receptor If this is due to the size of the VOC then the overall length may be the determining factor because on ascending a homologous series both the width and depth of the homologs remain constant It is interesting that odorant molecular length has been suggested as one factor in the olfactory code (Johnson and Leon 2000) Whatever the cause

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of the cut-off point it renders all equations for the correlation and prediction of EIT subject to a size restriction The only animal assay concerning VOCs is the very important lsquomouse assayrsquo first introduced by Alarie (Alarie 1966 1973 1981 1998 Alarie et al 1980) and developed into a standard test procedure for the estimation of sensory irritation (ASTM 1984) In the assay male Swiss-Webster mice are exposed to various vapor concentrations of a VOC and the concentration at which the respiratory rate is reduced by 50 is taken as the end-point and denoted as RD50 An evaluation of the use RD50 to establish acceptable exposure levels of VOCs in humans has recently been published (Kuwabara et al 2007) There were a number of attempts to relate RD50 values for a series of VOCs to physical properties of the VOCs such as the water-octanol partition coefficient Poct) or the gas-hexadecane partition coefficient but these relationships were restricted to particular homologous series (Nielsen and Alarie 1982 Nielsen and Bakbo 1985 Nielsen and Yamagiwa 1989 Nielsen et al 1990) A useful connection was between RD50 and the VOC saturated vapor pressure at 310 K viz RD50 VPo = constant (Nielsen and Alarie 1982) This is known as Fergusonrsquos rule (Ferguson 1939) and although it was claimed to have a rigorous thermodynamic basis (Brink and Posternak 1948) it is now known to be only an empirical relationship (Abraham et al 1994) RD50 values were also obtained using a different strain of mice male Swiss OF1 mice (De Ceaurriz et al 1981) and were used to obtain relationships between log (1 RD50) and VOC properties such as log Poct or boiling point for compounds that were classed as nonreactive (Muller and Gref 1984 Roberts 1986) The data used previously (Roberts 1986) were later fitted to Eqn 3 to yield Eqn 40 for unreactive compounds (Abraham et al 1990) Log (1FRD50) = -0596 + 1354 middot S + 3188 middot A + 0775 middot L

(N = 39 SD = 0103 R2 = 0980) (40)

FRD50 is in units of mmol m-3 rather than ppm but this affects only the constant in Eqn 40 The fine review of Schaper lists RD50 values for not only Swiss-Webster mice but also for Swiss OF1 mice (Schaper 1993) and an updated equation for Swiss OF1 mice in terms of RD50 was set out (Abraham 1996) Log (1RD50) = -671 + 130 middot S + 288 middot A + 076 middot L

(N = 45 SD = 0140 R2 = 0962 F = 350) (41)

The Schaper data base was used to test if log (1RD50) values for nonreactive VOCs could be correlated with gas to solvent partition coefficients as log K and reasonable correlations were found for a number of solvents (Abraham et al 1994 Alarie et al 1995 1996) In order to analyze values for a wide range of VOCs it was thought important to distinguish compounds that illicit an effect through a lsquochemicalrsquo mechanism or through a lsquophysicalrsquo mechanism these terms being equivalent to lsquoreactiversquo or lsquononreactiversquo (Alarie et al 1998a) The Ferguson rule was used to discriminate between the two classes if RD50 VPo gt 01 the VOC was deemed to act by a physical mechanism (p) and if RD50 VPo lt 01 the VOC was considered to act by a chemical mechanism (c) For 58 VOCs acting by a physical mechanism Eqn 42 was obtained (Alarie et al 1998b) for Swiss OF1 mice and Swiss-Webster mice

Log (1RD50) = -7049 + 1437 middot S + 2316 middot A + 0774 middot L

(N = 58 SD = 0354 R2 = 0840 F = 945) (42)

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A more recent analysis has been carried out (Luan et al 2006) using the previous data and division into physical and chemical mechanisms For 47 VOCs acting by a physical mechanism Eqn 43 was obtained Log (1RD50) = -5550 + 0043middot Re + 6329middot RPCG + 0377middot ICave + 0049middot CHdonor ndash 3826 middotRNSB + 0047middot ZX (N = 47 SD = 0362 R2 = 0844 F = 361)

(43)

The statistics of Eqn 43 are not as good as those of Eqn 42 and since some of the descriptors in Eqn 43 are chemically almost impossible to interpret (ICave is the average information content and ZX is the ZX shadow) it has no advantage over Eqn 42 What is of more interest is that it was possible to derive an equation for VOCs acting by a chemical mechanism (Luan et al 2006) Log (1RD50) = 8438 + 0214middot PPSA3 + 0017middot Hf ndash 22510middot Vcmax + 0229middot BIC + 44508middot (HDCA + 1TMSA) + 0049 middotBOminc (N = 67 SD = 0626 R2 = 0737 F = 280)

(44)

Although again Eqn 44 is chemically difficult to interpret it does show that it is possible to estimate RD50 values for VOCs that are reactive and act through a chemical mechanism About 20 million patients receive a general anesthetic each year in the USA In spite of considerable effort the specific site of action of anesthetics is still not well known However even if the actual site of action is not known it is possible that a general mechanism on the lines shown in Figure 4 obtains In the first stage the anesthetic is transported from the gas phase to a site of action and in the second stage interaction takes place with a target receptor a variety of which have been suggested ((Franks 2006 Zhang et al 2007 Steele et al 2007) Then if stage 1 is a major component we might expect that a QSAR could be constructed for inhalation anesthesia It is noteworthy that a QSAR on the lines of Eqn 2 was constructed for aqueous anesthesia as long ago as 1991 (Abraham et al 1991) Since then rather little has been achieved in terms of inhalation anesthesia The usual end point in inhalation anesthesia is the minimum alveolar concentration MAC of an inhaled anesthetic agent that prevents movement in 50 of subjects in response to noxious stimulation In rats this is electrical or mechanical stimulation of the tail MAC values are expressed in atmospheres and correlations are carried out using log (1MAC) so that the smaller is MAC the more potent is the anesthetic It was shown (Sewell and Halsey 1997) that shape similarity indices gave better fits for log (1MAC) than did gas to olive oil partition coefficients but the analysis was restricted to a model for 10 fluoroethanes for which R2 = 0939 and a different model for 8 halogenated ethers for which R2 = 0984 was found A completely different model of inhalation anesthesiahas been put forward (Sewell and Sear 2004 2006) in which no consideration is taken as to how a gaseous solute is transported to a receptor but solute-receptor interactions are calculated However two different receptor models were needed one for a particular set of nonhalogenated compounds and one for a particular set of halogenated compounds so the generality of the model seems quite restricted A QSAR for inhalation anesthesia was eventually obtained using the LFER Eqn 3 as follows (Abraham et al 2008)

Log (1MAC) = - 0752 - 0034 middot E + 1559 middot S + 3594middot A + 1411 middot B + 0687 middot L

(N = 148 SD = 0192 R2 = 0985 F = 18561) (45)

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The only compounds not included in Eqn 45 were 112233445566-dodecafluorohexane and 223344556677-dodecafluoroheptan-1-ol which were known to be subject to cut-off effects and 1-octanol where the observed MAC value was subject to a greater error than usual Hence Eqn 45 is a very general equation and it can be suggested that stage 1 in Figure 4 does indeed represent the main process A related biological end point to inhalation anesthesia is that of convulsant activity It has been observed that a number of compounds expected to exhibit anesthesia actually provoke convulsions in rats (Eger et al 1999) The end point as for inhalation anesthesia is taken as the compound vapor pressure in atm that just induces convulsion CON Eqn 3 was applied to the observed data yielding Eqn 46 (Abraham and Acree 2009) Log (1CON) = -0573 -0228 middot E + 1198 middot S + 3232 middot A + 3355 middot B + 0776 middot L

(N = 44 SD = 0167 R2 = 0978 F = 3442) (46)

In terms of structural features it was shown that the anesthetics tended to have large hydrogen bond acidities whereas convulsants tended to have zero or small hydrogen bond acidities The only other notable structural feature was that convulsants had larger values of L and anesthetics tended to have smaller values of L Since L is somewhat related to size the convulsants are generally larger than the inhalation anesthetics

Fig 6 Plots of VOC activity Y against VOC carbon number N illustrating the use of an indicator variable I

It was pointed out (Abraham et al 2010c) that a large number of equations on the lines of Eqn 3 for various biological and toxicological effects of VOCs had been constructed these equations mainly representing stage 1 in Figure 4 Since this stage refers to the transfer of a VOC from the gas phase to some biological phase it was argued that it might be possible to amalgamate all these equations into one general equation for the biological and toxicological activity of VOCs Consider plots of toxicological activity Y against the number of carbon atoms N in a homologous series of VOCs If the two lines are parallel then a simple indicator variable I could be used to bring then both on the same line as shown in Figure 6 If the two lines are not parallel then after use an indicator variable they will appear as

N

Y

1086420

40

30

20

10

0

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shown in Figure 7 But even in this situation a general equation (or general line) might be used to correlate both sets of data albeit with an increase in the regression standard deviation It remained to be seen exactly how much error was introduced by use of a general equation

N

Y

1086420

30

25

20

15

10

5

0

Fig 7 Plots of VOC activity Y against VOC carbon number N showing how a general equation may be used to correlate two sets of data that give rise to lines of different slope

Various sets of data on toxicological and biological activity Y for a number of processes were used to construct an equation in which a number of indicator variables I were used in order to fit all the sets of data into one equation The result was Eqn 51 (Abraham et al 2010c) Y = -7805 + 0056 middot E + 1587 middot S + 3431middot A + 1440middot B + 0754 middot L + 0553middot Idr +

+ 2777 middotIodt -0036middot Inpt + 6923middot Imac + 0440middot Ird50 + 8161middot Itad + 7437middot Icon + + 4959middot Idav

(N = 643 SD = 0357 R2 = 0992 F = 60830)

(47)

The lsquostandardrsquo process was taken as eye irritation thresholds as log (1EIT) for which no indicator variable was used The given processes and the corresponding indicator variables are shown in Table 5 There are two processes listed in Table 5 that have not been considered here The data on gaseous anesthesia on tadpoles were derived from aqueous anesthesia together with water to gas partition coefficients and so are indirect data and the compounds in the data set for inhalation anesthesia on mice cover a very restricted range of descriptors Of the 720 data points 77 were outliers Nearly all of these were VOCs classed as lsquoreactiversquo or lsquochemicalrsquo in respiratory tract irritation in mice or VOCs that acted by specific effects in odor detection thresholds The remaining 643 data points all refer to nonreactive VOCs or to VOCs that act through selective and not specific effects The SD value of 0357 in Eqn 47 is quite good by comparison to the various SD values for individual processes suggesting that the general equation has incorporated these with little loss in accuracy the predicted standard deviation in Eqn 47 is only 0357 log units The equation is scaled to eye irritation thresholds but it is noteworthy that the coefficient for the NPT indicator variable is nearly zero Thus EIT and NPT can be estimated through Eqn 48 for any nonreactive VOC for which the relevant descriptors are available

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Y = log (1EIT) = log (1NPT) = -7805 + 0056 middot E + 1587 middot S + 3431middot A + + 1440middot B + 0754 middot L

(48)

The Abraham general solvation model provides reasonably accurate mathematical correlations and predicitions for a number of important biological responses including Eye irritation thresholds (EIT) nasal irritation (pungency) thresholds (NPT) odor detection thresholds (ODT) inhalation anesthesia (rats) and convulsant actictivity (mice)

Activity Units Y I VOCs

Total Outliers

Eye irritation thresholds ppm log(1EIT) None 23 0

EIT from Draize scores ppm log(DPo) Idr 72 0

Odor detection thresholds ppm log(1ODT) Iodt 64 20

Nasal pungency thresholds ppm log(1NPT) Inpt 48 0

Inhalation anesthesia ( rats)

atm log(1MAC) Imac 147 0

Respiratory irritation (mice)

ppm log(1RD50) Ird50 147 53

Gaseous anesthesia (tadpoles) molL log(1C) Itad 130 4

Convulsant activity (rats)

atm log(1CON) Icon 44 0

Inhalation anesthesia (mice)

vol log(1vol) Idav 45 0

Total 720 77

Table 5 Toxicological and Biological Data on VOCs used to construct Eqn 47

7 References

Abraham M H amp McGowan J C (1987) The use of characteristic volumes to measure cavity terms in reversed phase liquid chromatography Chromatographia 23 (4) 243ndash246

Abraham M H Lieb W R amp Franks N P (1991) The role of hydrogen bonding in general anesthesia Journal of Pharmaceutical Sciences 80 (8) 719-724

wwwintechopencom


Abraham M H (1993a) Scales of solute hydrogen-bonding their construction and application to physicochemical and biochemical processes Chemical Society Reviews 22 (2) 73-83

Abraham M H (1993b) Application of solvation equations to chemical and biochemical processes Pure and Applied Chemistry 65 (12) 2503-2512

Abraham M H amp Acree W E Jr(2009) Prediction of convulsant activity of gases and vapors European Journal of Medicinal Chemistry 44 (2) 885-890

Abraham M H Nielsen G D amp Alarie Y (1994) The Ferguson principle and an analysis of biological activity of gases and vapors Journal of Pharmaceutical Sciences 83 (5) 680-688

Abraham M H (1996) The potency of gases and vapors QSARs ndash anesthesia sensory irritation and odor in Indoor Air and Human Health Ed R B Gammage and B A Berven 2nd Ed CRC Lewis Publishers Boca Raton USA

Abraham M H Kumarsingh R Cometto-Muntildeiz J E amp Cain W S (1998a) A quantitative structure-activity relationship for a Draize eye irritation database Toxicology in Vitro 12 (3) 201-207

Abraham M H Kumarsingh R Cometto-Muntildeiz J E amp Cain W S (1998b) Draize eye scores and eye irritation thresholds in man combined into one quantitative structure-activity relationship Toxicology in Vitro 12 (4) 403-408

Abraham M H Kumarsingh R Cometto-Muntildeiz J E amp Cain W S (1998c) An algorithm for nasal pungency thresholds in man Archives of Toxicology 72 (4) 227-232

Abraham M H Gola J M R Cometto-Muntildeiz J Eamp Cain W S (2001) The correlation and prediction of VOC thresholds for nasal pungency eye irritation and odour in humans Indoor Built Environment 10 (3-4) 252-257

Abraham M H Gola J M R Cometto-Muntildeiz J Eamp Cain W S (2002) A model for odour thresholds Chemical Senses 27 (2) 95-104

Abraham M H Hassanisadi M Jalali-Heravi M Ghafourian T Cain W S amp Cometto-Muntildeiz J E (2003) Draize rabbit eye test compatibility with eye irritation thresholds in humans a quantitative structure-activity relationship analysis Toxicological Sciences 76 (2) 384-391

Abraham M H Ibrahim A amp Zissimos A M (2004) Determination of sets of solute descriptors from chromatographic measurements Journal of Chromatography A 1037 (1-2) 29-47

Abraham M H Ibrahim A Zhao Y Acree W E Jr (2006) A data base for partition of volatile organic compounds and drugs from bloodplasmaserum to brain and an LFER analysis of the data Journal of Pharmaceutical Sciences 95 (10) 2091-2100

Abraham M H Acree W E Jr Mintz C amp Payne S (2008) Effect of anesthetic structure on inhalation anesthesia implications for the mechanism Journal of Pharmaceutical Sciences 97 (6) 2373-2384

Abraham M H Gil-Lostes J amp Fatemi M (2009a) Prediction of milkplasma concentration ratios of drugs and environmental pollutants European Journal of Medicinal Chemistry 44 (6) 2452-2458

Abraham M H Acree W E Jr amp Cometto-Muntildeiz J E (2009b) Partition of compounds from water and from air into amides New Journal of Chemistry 33 (10) 2034-2043

wwwintechopencom


Abraham MH Smith RE Luchtefeld R Boorem AJ Luo R amp Acree WE Jr (2010a) Prediction of solubility of drugs and other compounds in organic solvents Journal of Pharmaceutical Sciences 99 (3) 1500-1515

Abraham M H Saacutenchez-Moreno R Gil-Lostes J Cometto-Muntildeiz J E amp Cain W S (2010b) Physicochemical modeling of sensory irritation in humans and experimental animals Chapter 25 pp 378-389 in Toxicology of the Nose and Upper Airways Ed J B Morris and D J Shusterman Informa Healthcare New York USA

Abraham M H Saacutenchez-Moreno R Gil-Lostes J Acree W E Jr Cometto-Muntildeiz J E amp Cain W S (2010c)The biological and toxicological activity of gases and vapors Toxicology in Vitro 24 (2) 357-362

ADME Boxes version (2010) Advanced Chemistry Development 110 Yonge Street 14th Floor Toronto Ontario M5C 1T4 Canada

Alarie Y (1966) Irritating properties of airborne materials to the upper respiratory tract Archives Environmental Health 13 (4) 433-449

Alarie Y(1973) Sensory irritation by airborne chemicals CRC Critical Reviews in Toxicology 2 (3) 299-363

Alarie Y (1981) Dose-response analysis in animal studies prediction of human response Environmental Health Perspective 42 (Dec) 9-13

Alarie Y (1998) Computer-based bioassay for evaluation of sensory irritation of airborne chemicals and its limit of detection Archives of Toxicology 72 (5) 277-282

Alarie Y Kane L amp Barrow C (1980) Sensory irritation the use of an animal model to establish acceptable exposure to airborne chemical irritants in Toxicology Principles and Practice Vol 1 Ed Reeves A L John Wiley amp Sons Inc New York

Alarie Y Nielsen G D Andonian-Haftvan J amp Abraham M H (1995) Physicochemical properties of nonreactive volatile organic chemicals to estimate RD50 alternatives to animal studies Toxicology and Applied Pharmacology 134 (1) 92-99

Alarie Y Schaper M Nielsen G D amp Abraham M H (1996) Estimating the sensory irritating potency of airborne nonreactive volatile organic chemicals and their mixtures SAR and QSAR in Environmental Research 5 (3) 151-165

Alarie Y Nielsen G D amp Abraham M H (1998a) A theoretical approach to the Ferguson principle and its use with non-reactive and reactive airborne chemicals Pharmacology and Toxicology 83 (6) 270-279

Alarie Y Schaper M Nielsen G D amp Abraham M H (1998b) Structure-activity relationships of volatile organic compounds as sensory irritants Archives of Toxicology 72 (3) 125-140

American Society for Testing and Materials (1984) Standard test method for estimating sensory irritancy of airborne chemicals Designation E981-84 American Society for Testing and Materials Philadelphia Pa USA

Andrade RJ Lucena MI Martin-Vivaldi R Fernandez MC Nogueras F Pelaez G Gomez-Outes A Garcia-Escano MD Bellot V amp Hervas A (1999) Acute liver injury associated with the use of ebrotidine a new H2-receptor antagonist Journal of Hepatology 31 (4) 641-646

Bowen KR Flanagan KB Acree WE Jr Abraham MH amp Rafols C (2006) Correlation of the toxicity of organic compounds to tadpoles using the Abraham model Science of the Total Environmen 371 (1-3) 99-109

wwwintechopencom


Brink F amp Posternak J M (1948) Thermodynamic analysis of the relative effectiveness of narcotics Journal of Cell Comparative Physiology 32 211-233

Chaput J-P amp Tremblay A (2010) Well-being of obese individuals therapeutic perspectives Future Medicinal Chemistry 2 (12) 1729-1733

Charlton AK Daniels CR Acree WE Jr amp Abraham MH (2003) Solubility of Crystalline Nonelectrolyte Solutes in Organic Solvents Mathematical Correlation of Acetylsalicylic Acid Solubilities with the Abraham General Solvation Model Journal of Solution Chemistry 32 (12) 1087-1102

Cometto-Muntildeiz JE (2001) Physicochemical basis for odor and irritation potency of VOCs In Indoor Air Quality Handbook (Spengler JD et al eds) pp 201-2021 New York McGraw-Hill

Cometto-Muntildeiz JE amp Abraham M H (2008) A cut-off in ocular chemesthesis from vapors of homologous alkylbenzenes and 2-ketones as revealed by concentration-detection functions Toxicology and Applied Pharmacology 230 (3) 298-303

Cometto-Muntildeiz JE amp Abraham M H (2009a) Olfactory detectability of homologous n-alkylbenzenes as reflected by concentration-detection functions in humans Neuroscience 161 (1) 236-248

Cometto-Muntildeiz JE amp Abraham M H (2009b) Olfactory psychometric functions for homologous 2-ketones Behavioural Brain Research 201 (1) 207-215

Cometto-Muntildeiz JE amp Abraham M H (2010a) Structure-activity relationships on the odor detectability of homologous carboxylic acids by humans Experimental Brain Research 207 (1-2) 75-84

Cometto-Muntildeiz JE amp Abraham M H (2010b) Odor detection by humans of lineal aliphatic aldehydes and helional as gauged by dose-response functions Chemical Senses 35 (4) 289-299

Cometto-Muntildeiz J E amp Cain W S (1991) Nasal pungency odor and eye irritation thresholds for homologous acetates Pharmacology Biochemistry and Behavior 39 (4) 983-989

Cometto-Muntildeiz J E amp Cain W S (1995) Relative sensitivity of the ocular trigeminal nasal trigeminal and olfactory systems to airborne chemicals Chemical Senses 20 (2) 191-198

Cometto-Muntildeiz J E amp Cain W S (1998) Trigeminal and olfactory sensitivity comparison of modalities and methods of measurement International Archives of Occupational and Environmental Health 71 (2) 105-110

Cometto-Muntildeiz J E Cain W S amp Hudnell H K (1997) Agonistic sensory effects of airborne chemicals in mixtures odor nasal pungency and eye irritation Perception amp Psychophysics 59 (5) 665-674

Cometto-Muntildeiz J E Cain W S Abraham M H amp Kumarsingh R (1998a) Sensory properties of selected terpenes Thresholds for odor nasal pungency nasal localizations and eye irritation Annals of the New York Academy of Sciences 855 (Olfaction and Taste XII) 648-651

Cometto-Muntildeiz J E Cain W S Abraham M H amp Kumarsingh R (1998b) Trigeminal and olfactory chemosensory impact of selected terpenes Pharmacology and Biochemistry and Behaviour 60 (3) 765-770

Cometto-Muntildeiz J E Cain W S amp Abraham M H (2005a) Determinants for nasal trigeminal detection of volatile organic compounds Chemical Senses 30 (8) 627-642

wwwintechopencom


Cometto-Muntildeiz J E Cain W S amp Abraham M H (2005b) Molecular restrictions for human eye irritation by chemical vapors Toxicology and Applied Pharmacology 207 (3) 232-243

Cometto-Muntildeiz J E Cain W S Abraham M H amp Saacutenchez-Moreno R (2006) Chemical boundaries for detection of eye irritation in humans from homologous vapors Toxicological Sciences 91 (2) 600-609

Cometto-Muntildeiz J E Cain W S Abraham M H amp Saacutenchez-Moreno R (2007a) Cutoff in detection of eye irritation from vapors of homologous carboxylic acids and aliphatic aldehydes Neuroscience 145 (3) 1130-1137

Cometto-Muntildeiz J E Cain W S Abraham M H amp Saacutenchez-Moreno R (2007b) Concentration-detection functions for eye irritation evoked by homologous n-alcohols and acetates approaching a cut-off point Experimental Brain Research 182 (1) 71-79

Cometto-Muntildeiz J E Cain W S Abraham M H Saacutenchez-Moreno R amp Gil-Lostes J (2010)Nasal Chemosensory Irritation in Humans Chapter 12 pp 187-202 in Toxicology of the Nose and Upper Airways Ed J B Morris and D J Shusterman Informa Healthcare New York USA

Daniels CR Charlton AK Wold RM Pustejovsky E Furman AN Bilbrey AC Love JN Garza JA Acree WE Jr amp Abraham MH (2004a) Mathematical correlation of naproxen solubilities in organic solvents with the Abraham solvation parameter model Physics and Chemistry of Liquids 42 (5) 481-491

Daniels CR Charlton AK Acree WE Jr amp Abraham MH (2004b) Thermochemical behavior of dissolved Carboxylic Acid solutes Part 2 - Mathematical Correlation of Ketoprofen Solubilities with the Abraham General Solvation Model Physics and Chemistry of Liquids 42 (3) 305-312

De Ceaurriz J C Micillino J C Bonnet P amp Guenier J P (1981) Sensory irritation caused by various industrial airborne chemicals Toxicology Letters 9 (2)137-143

Diettrich S Ploessi F Bracher F amp Laforsch C (2010) Single and combined toxicity of pharmaceuticals at environmentally relevant concentrations in Daphnia Magna ndash a multigeneration study Chemosphere 79 (1) 60-66

Doty R L Cometto-Muntildeiz J E Jalowayski A A Dalton P Kendal-Reed M amp Hodgson M (2004) Assessment of Upper Respiratory Tract and Ocular Irritative Effects of Volatile Chemicals in Humans Critical Reviews in Toxicology 43 (2) 85-142

Draize J H Woodward G amp Calvery H O (1944) Methods for the study of irritation and toxicity of substances applied topically to the skin and mucous membranes Journal of Pharmacology 82 (3) 377-390

Edwards JO amp Curci R (1992) Fenton type activation and chemistry of hydroxyl radical In Catalytic oxidation with hydrogen peroxide as oxidant Struckul (ed) Kluwer Academic Publishers Netherlands pp 97ndash151

Escher BI Baumgartner B Koller M Treyer K Lienent J amp McAndell C S (2011) Environmental Toxicology and Risk Assessment of Pharmaceuticals from Hospital Wastewaters Water Research 45 (1) 75-92

Eger II E I Koblin D D Sonner J Gong D Laster M J Ionescu P Halsey M J amp Hudlicky T (1999) Nonimmobilizers and transitional compounds may produce convulsions by two mechanisms Anesthesia amp Analgesia 88 (4) 884-892

wwwintechopencom


Famini G R Agular D Payne M A Rodriquez R amp Wilson L Y (2002) Using the theoretical linear solvation energy relationships to correlate and to predict nasal pungency thresholds Journal of Molecular Graphics amp Modelling 20 (4) 277-280

Ferguson J (1939) The use of chemical potentials as indices of toxicity Proceedings of the Royal Society of London Series B 127 387-404

Forbes B Hashmi N Martin GP amp Lansley AB (2000) Formulation of inhaled medicines effect of delivery vehicle on immortalized epithelial cells Journal of Aerosol Medicine 13 (3) 281ndash288

Fourches D Barnes JC Day NC Bradley P Reed JZ amp Tropsha A (2010) Cheminformatics analysis of assertations mined from literature that describe drug-induced liver injury in different species Chemical Research in Toxicology 23 (1) 171-183

Franks N P (2006) Molecular targets underlying general anesthesia British Journal of Pharmacology 147 (Suppl 1) S72-S81

Gad-Allah TA Ali MEM amp Badawy MI (2011) Photocatytic oxidation of ciprofloxacin under simulated sunlight Journal of Hazardous Materials 186 (1) 751-755

Goldkind L amp Laine L (2006) A systematic review of NSAIDs withdrawn from the market due to hepatotoxicity lessons learned from the bromfenac experience Pharmacoepidemiology and Drug Safety 15 (4) 213-220

Gunatilleka AD amp Poole CF (1999) Models for estimating the non-specific aquatic toxicity of organic compounds Analytical Communications 36 (6) 235-242

Gursoy RN amp Benita S (2004) Self-emulsifying drug delivery systems (SEDDS) for improved oral delivery of lipophilic drugs Biomedicine and Pharmacotherapy 58 (3) 173ndash182

Han S Choi K Kim J Ji K Kim S Ahn B Yun J Choi K Khim JS Zhang X amp Glesy JP (2010) Endocrine disruption and consequences of chronic exposure to ibuprofen in Japanese medaka (Oryzias latipes) and freshwater cladocerans Daphnia magna and Moina macrocopa Aquatic Toxicology 98 (3) 256-264

Hoover KR Acree WE Jr amp Abraham MH (2005) Chemical toxicity correlations for several fish species based on the Abraham solvation parameter model Chemical Research in Toxicology 18 (9) 1497-1505

Hoover KR Flanagan KB Acree WE Jr amp Abraham Michael H (2007) Chemical toxicity correlations for several protozoas bacteria and water fleas based on the Abraham solvation parameter model Journal of Environmental Engineering and Science 6 (2) 165-174

Hoye JA amp Myrdal PB (2008) Measurement and correlation of solute solubility in HFA- 134aethanol systems International Journal of Pharmaceutics 362 (1-2) 184-188

Huang CP Dong C amp Tang Z (1993) Advanced chemical oxidation its present role and potential in hazardous waste treatment Waste Mangement 13 (5-7) 361ndash377

Isidori M Lavorgna M Nardelli A Pascarella L amp Parrella A (2005) Toxic and genotoxic evaluation of six antibiotics on nontarget organisms Science of the Total Environment 346 (1-3) 87ndash98

Johnson B A amp Leon M (2000) Odorant Molecular Length One Aspect of the Olfactory Code Journal of Comparative Neurology 426 (2) 330-338

wwwintechopencom


Jover J Bosque R amp Sales J (2004) Determination of the Abraham solute descriptors from molecular structure Journal of Chemical Information and Computer Science 44 (3) 1098-1106

Khetan SK amp Colins TJ (2007) Human pharmaceuticals in the aquatic environment a challenge to green chemistry Chemical Reviews 107 (6) 2319-2364

Kulik N Trapido M Goi A Veressinina Y amp Munter Y (2008) Combined chemical treatment of pharmaceutical effluents from medical ointment production Chemosphere 70 (8) 1525-1531

Kuwabara Y Alexeeff G V Broadwin R amp Salmon AG (2007) Evaluation and Application of the RD50 for determining acceptable exposure levels of airborne sensory irritants for the general public Environmental Health Perspective 115 (11) 1609-1616

Lamarche O Platts JA amp Hersey A (2001) Theoretical prediction of the polaritypolarizability parameter π2H Physical Chemistry Chemical Physics 3 (14) 2747-2753

Lammert C Einarsson S Saha C Niklasson A Bjornsson E amp Chalasani N (2008) Relationship between daily dose of oral medications and idiosyncratic drug-induced liver injury search for signals Hepatology 47 (6) 2003-2009

Lemus J A Blanco G Arroyo B Martinez F Grande J (2009) Fatal embryo chondral damage associated with fluoroquinolones in eggs of threatened avian scavengers Environmental Pollution 157 (8-9) 2421-2427

Luan F G Guo L Cheng Y Li X amp Xu X (2010) QSAR relationship between nasal pungency thresholds of volatile organic compounds and their molecular structure Yantai Daxue Xuebao Ziran Kexue Yu Gongchengban 23 (4) 272-276

Luan F Ma W Zhang X Zhang H Liu M Hu Z amp Fan B T (2006) Quantitative structure-activity relationship models for prediction of sensory irritants (log RD50) of volatile organic chemicals Chemosphere 63 (7) 1142-1153

Mintz C Clark M Acree W E Jr amp Abraham M H (2007) Enthalpy of solvation correlations for gaseous solutes dissolved in water and in 1-octanol based on the Abraham model Journal of Chemical Information and Modeling 47 (1) 115-121

Morris J B amp Shusterman (2010) Toxicology of the Nose and Upper Airways Informa Healthcare New York USA

Muller J amp Gref G (1984) Recherche de relations entre toxicite de molecules drsquointeret industriel et proprietes physico-chimiques test drsquoirritation des voies aeriennes superieures applique a quatre familles chimique Food and Chemical Toxicology 22 (8) 661-664

Naidoo V Venter L Wolter K Taggart M amp Cuthbert R (2010a) The toxicokinetics of ketoprofen in Gyps coprotheres toxicity due to zero-order metabolism Archives of Toxicology 84 (10) 761-766

Naidoo V Wolter K Cromarty D Diekmann M Duncan N Meharg A A Taggart M A Venter L amp Cuthbert R (2010b) Toxicity of non-steroidal anti-inflammatory drugs to Gyps vultures a new threat from ketoprofen Biology Letters 6 (3) 339-341

Nielsen G D amp Alarie Y (1982) Sensory irritation pulmonary irritation and respiratory simulation by airborne benzene and alkylbenzenes prediction of safe industrial exposure levels and correlation with their thermodynamic properties Toxicology and Applied Pharmacology 65 (3) 459-477

wwwintechopencom


Nielsen G D amp Bakbo J V (1985) Sensory irritating effects of allyl halides and a role for hydrogen bonding as a likely feature of the receptor site Acta Pharmacologica et Toxicologica 57 (2) 106-116

Nielsen G D amp Yamagiwa M (1989) Structure-activity relationships of airway irritating aliphatic amines Receptor activation mechanisms and predicted industrial exposure limits Chemico-Biological Interactions 71 (2-3) 223-244

Nielsen G D Thomsen E S amp Alarie Y (1990) Sensory irritant receptor compartment properties Acta Pharmaceutica Nordica 1 (2) 31-44

Nikolaou A Meric S amp Fatta D (2005) Occurrence patterns of pharmaceuticals in water and wastewater environments Analytical and Bioanalytical Chemistry 387 (4) 1225-1234

Ozer JS Chetty R Kenna G Palandra J Zhang Y Lanevschi A Koppiker N Souberbielle BE amp Ramaiah SK (2010) Enhancing the utility of alanine aminotransferase as a reference standard biomarker for drug-induced liver injury Regulatory Toxicology and Pharmacology 56 (3) 237-246

Paje ML Kuhlicke U Winkler M amp Neu TR (2002) Inhibition of lotic biofilms by diclofenac Applied Microbiology and Biotechnology 59 (4-5) 488-492

Patton JS amp Byron P R (2007) Inhaling medicines delivering drugs to the body through the lungs National Reviews Drug Discovery 6 (1) 67ndash74

Platts JA Butina D Abraham MH amp Hersey A (1999) Estimation of molecular linear free energy relation descriptors using a group contribution approach Journal of Chemical Information and Computer Sciences 39 (5) 835-845

Platts JA Abraham MH Butina D amp Hersey A (2000) Estimation of molecular linear free energy relationship descriptors by a group contribution approach 2 Prediction of partition coefficients Journal of Chemical Information and Computer Sciences 40 (1) 71-80

Ramos EU Vaes WHJ Verhaar HJM amp Hermens JLM (1998) Quantitative structure-activity relationships for the aquatic toxicity of polar and nonpolar narcotic pollutants Journal of Chemical Information and Computer Science 38 (5) 845-852

Roberts D W (1986) QSAR for upper respiratary tract irritation Chemical-Biological Interactions 57 (3) 325-345

Sanderson H amp Thomsen M (2009) Comparative Analysis of pharmaceuticals versus industrial chemicals acute aquatic toxicity classification according to the United Nations classification system for chemicals Assessment of (Q)SAR predictability of pharmaceuticals acute aquatic toxicity and their predominant acute toxicity mode-of action Toxicology Letters 187 (2) 84-93

Schaper M (1993) Development of a data base for sensory irritants and its use in establishing occupational exposure limits American Industrial Hygiene Association Journal 54 (9) 488-544

Schultz TW Yarbrough JW amp Pilkington TB (2007) Aquatic toxicity and abiotic thiol reactivity of aliphatic isothiocyanates Effects of alkyl-size and ndashshape Environmental Toxicology and Pharmacology 23 (1) 10-17

Sell C S (2006) On the unpredictability of odor Angewandte Chemie International Edition 45 (38) 6254-6261

wwwintechopencom


Sewell JC amp Halsey MJ (1997) Shape similarity indices are the best predictors of substituted fluorethane and ether anaesthesia European Journal of Medicinal Chemistry 32 (9) 731-737

Sewell JC amp Sear JW (2004) Derivation of preliminary three-dimensional pharmacophores for nonhalogenated volatile anesthetics Anesthesia amp Analgesia 99 (3) 744-751

Sewell JC amp Sear JW (2006) Determinants of volatile general anesthetic potency A preliminary three-dimensional pharmacophore for halogenated anesthetics Anesthesia amp Analgesia 102 (3) 764-771

Shaw RJ (1999) Inhaled corticosteroids for adult asthma impact of formulation and delivery device on relative pharmacokinetics efficacy and safety Respiratory Medicine 93 (3) 149ndash160

Shi S amp Klotz U (2008) Clinical use and pharmacological properties of Selective COX-2 inhibitors European Journal of Clinical Pharmacology 64 (3) 233-252

Stovall DM Givens C Keown S Hoover KR Rodriguez E Acree WE Jr amp Abraham MH (2005) Solubility of Crystalline Nonelectrolyte Solutes in Organic Solvents Mathematical Correlation of Ibuprofen Solubilities with the Abraham Solvation Parameter Model Physics and Chemisry of Liquids 43 (3) 261-268

Smyth HDC (2003) The influence of formulation variables on the performance of alternative propellant-driven metered dose inhalers Advanced Drug Delivery Reviews 55(7) 807-828

Steele L M Morgan P G amp Sendensky M M (2007) Genetics and the mechanisms of action of inhaled anesthetics Current Pharmacogenomics 5 (2) 125-141

Taggart MA Senacha KR Green RE Cuthbert R Jhala YV Meharg AA Mateo R amp Pain DJ (2009) Analysis of nine NSAIDs in ungulate tissues available to critically endangered vultures in India Environmental Science and Technology 43(12) 4561-4566

Tang B Cheng G Gu J-C amp Xu J-C (2008) Development of solid self-emulsifying drug delivery systems preparation techniques and dosage forms Drug Discovery Today 13 (13-14) 606ndash612

Tauxe-Wuersch A De Alencastro LF Grandjean D amp Tarradellas J (2005) Occurrence of several acidic drugs in sewage treatment plants in Switzerland and risk assessment Water Research 39 (9) 1761-1772

Tekin H Bilkay O Ataberk SS Balta TH Ceribasi IH Sanin FD Dilek FB amp Yetis U (2006) Use of Fenton oxidation to improve the biodegradability of a pharmaceutical wastewater Journal of Hazardous Materials B136 (2) 258-265

Triebskorn R Casper H Heyd A Eibemper R Koumlhler H-R amp Schwaiger J (2004) Toxic effects of the non-steroidal anti-inflammatory drug diclofenac Part II Cytological effects in liver kidney gills and intestine of rainbow trout (Oncorhynchus mykiss) Aquatic Toxicology 68 (2) 151-166

Tsagogiorgas C Krebs J Pukelsheim M Beck G Yard B Theisinger B Quintel M amp Luecke T (2010) Semifluorinated alkanes - A new class of excipients suitable for pulmonary drug delivery European Journal of Pharmaceutics and Biopharmaceutics 76 (1) 75-82

wwwintechopencom


van Noort PCM Haftka JJH amp Parsons JR (2010) Updated Abraham solvation parameters for polychlorinated biphenyls Environmental Science and Technology 44 (18) 7037-7042

Veithen A Wilkin F Philipeau Mamp Chatelain P (2009) Human olfaction from the nose to receptors Perfumer amp Flavorist 34 (11) 36-44

Veithen A Wilkin F Philipeau M Van Osselaare C amp Chatelain P (2010) From basic science to applications in flavors and fragrances Perfumer amp Flavorist 35 (1) 38-43

Von der Ohe PC Kuumlhne R Ebert R-U Altenburger R Liess M amp Schuumluumlrmann G (2005) Structure alerts ndash a new classification model to discriminate excess toxicity from narcotic effect levels of organic compounds in the acute daphnid assay Chemical Research in Toxicology 18 (3) 536ndash555

Wilson D A amp Stevenson R J (2006) Learning to Smell Johns Hopkins University |Press Baltimore USA

Zhang T Reddy K S amp Johansson J S (2007) Recent advances in understanding fundamental mechanisms of volatile general anesthetic action Current Chemical Biology 1 (3) 296-302

Zissimos AM Abraham MH Barker MC Box KJ amp Tam KY (2002a) Calculation of Abraham descriptors from solvent-water partition coefficients in four different systems evaluation of different methods of calculation Journal of the Chemical Society Perkin Transactions 2 (3) 470-477

Zissimos AM Abraham MH Du CM Valko K Bevan C Reynolds D Wood J amp Tam KY (2002b) Calculation of Abraham descriptors from experimental data from seven HPLC systems evaluation of five different methods of calculation Journal of the Chemical Society Perkin Transactions 2 (12) 2001-2010

Zissimos AM Abraham MH Klamt A Eckert F amp Wood (2002a) A comparison between two general sets of linear free energy descriptors of Abraham and Klamt Journal of Chemical Information and Computer Sciences 42 (6) 1320-1331

wwwintechopencom

Toxicity and Drug TestingEdited by Prof Bill Acree

ISBN 978-953-51-0004-1Hard cover 528 pagesPublisher InTechPublished online 10 February 2012Published in print edition February 2012

InTech EuropeUniversity Campus STeP Ri Slavka Krautzeka 83A 51000 Rijeka Croatia Phone +385 (51) 770 447 Fax +385 (51) 686 166wwwintechopencom

InTech ChinaUnit 405 Office Block Hotel Equatorial Shanghai No65 Yan An Road (West) Shanghai 200040 China

Phone +86-21-62489820 Fax +86-21-62489821

Modern drug design and testing involves experimental in vivo and in vitro measurement of the drugcandidates ADMET (adsorption distribution metabolism elimination and toxicity) properties in the earlystages of drug discovery Only a small percentage of the proposed drug candidates receive governmentapproval and reach the market place Unfavorable pharmacokinetic properties poor bioavailability andefficacy low solubility adverse side effects and toxicity concerns account for many of the drug failuresencountered in the pharmaceutical industry Authors from several countries have contributed chaptersdetailing regulatory policies pharmaceutical concerns and clinical practices in their respective countries withthe expectation that the open exchange of scientific results and ideas presented in this book will lead toimproved pharmaceutical products

How to referenceIn order to correctly reference this scholarly work feel free to copy and paste the following

William E Acree Jr Laura M Grubbs and Michael H Abraham (2012) Prediction of Toxicity SensoryResponses and Biological Responses with the Abraham Model Toxicity and Drug Testing Prof Bill Acree(Ed) ISBN 978-953-51-0004-1 InTech Available from httpwwwintechopencombookstoxicity-and-drug-testingprediction-of-toxicity-sensory-responses-and-biological-responses-with-the-abraham-model


warfarin withdrawn in from US market in 2006) troglitazone (an anti-diabetic and anti-inflammatory drug withdrawn from the UK market in 1997 and US market in 2000) ebrotidine (an H2-reciptor antagonist marketed in Spain in 1997 withdrawn from the market in 1998) ticrynafen (a diuretic drug used in treatment of hypertension withdrawn from US market in 1979) benoxaprofen (a nonsteroidal anti-inflammatory drug withdrawn from US market in 1982) ibufenac (nonsteroidal anti-inflammatory drug used for the treatment of Rheumatoid arithritis withdrawn from UK market in 1970) and bromfenac (a nonsteroidal anti-inflammatory drug introduced in 1997 as a short-term analgesic for orthopedic pain withdrawn from the market in 1998) (Lamment et al 2008 Andrade et al 1999 Goldkind and Laine 2006) Other drugs such as valproic acid ketoconazole nicotinic acid rifampin chlorzoxazone isoniazid dantrolene nefazodone telethromycin nevirapine atomoxetine and inflixmab have received strong heptatoxicity warnings from the US Food and Drug Administration (Lamment et al 2008) Sibutramine and phenylpropanolamine used in the treatment of obesity were removed from the US market due to adverse effects associated with cardiovascular disease and hemorrhagic stroke respectively (Chaput and Tremblay 2010) Additional drugs withdrawn from the market for cardiovascular toxicities and concerns include rotecoxib (used to relieve acute pain and symptoms of chronic inflammation removed from market in 2005) and valdecoxib (used to relieve acute pain and symptoms of chronic inflammation removed from market in 2005) (Shi and Klotz 2008) Toxicity screening identifies drug candidates that exhibit predictableintrinsic drug-induced liver injury Idiosyncratic DILI occurs infrequently and only in treated patients which are highly susceptible to the given pharmaceutical compound Conventional preclinical safety testing is not the best method to detect idiosyncratic DILI Fourches and coworkers (2010) examined the possibility of using laboratory test animals as viable means to screen drug candidates for possible drug-induced liver injuries The authors compiled a data set of 951 compounds reported to induce a wide range of liver effects in humans and in different animal species Of the 951 compounds considered 650 had been identified as causing liver effects in humans 685 had been reported in the literature as causing liver effects in rodents and only 166 had shown liver effects in nonrodents The concordance between two species CONC(species A species) was defined as

( ) ( )

( )Toxic for both Aand B Nontoxic for both Aand B

CONC species A speciesBTotalnumber of compoundsstudied

(1)

as the number of compounds that exhibited toxicity for both animal species plus the number of compounds that showed notoxicity for both animal species divided by the total number of compounds considered Equation 1 was applied to the liver effect data gathered from the published literature The authors found a relatively low concordance of between 39 to 44 between different species ndash for human + rodents the concordance was equal to 442 ((402 + 18)951) and for human + nonrodents that concordance was equal to 399 ((122+257)951) Animal testing while informative does not necessarily provide an accurate indication of the pharmaceutical compoundrsquos likelihood to produce a liver effect in humans For the concordance calculations it was assumed that the pharmaceutical compound had been tested on all three species groups The above calculations further underscore the importance of finding suitable testing methods and models for use in drug discovery Drug safety considerations also include unwanted side effects and the impact that the pharmaceutical product will have on environment A significant fraction of the

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C 1635

N 1439

O 1243

Si 2683 P 2487 S 2291

Ge 3102 As 2942 Se 2781

Sn 3935 Sb 3774 Te 3614

Pb 4344 Bi 4219

H 871 He 676 B 1832

F 1048 Ne 851 Hg 3400

Cl 2095 Ar 1900

Br 2621 Kr 2460

I 3453 Xe 3290

Rn 3840



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L = ndash 0882 + 1183 E + 0839 S + 0454 A + 0157 B + 3505 V (7)

(N = 4785 SD = 031 R2 = 0992 F = 115279)








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treatments














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(N= 196 SD = 0276 R2 = 0953 F = 7794) (11)


(12)


(13)


(14)


(15)

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(16)


(17)












(18)


(19)


(20)


(21)


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H2O2 + h ------gt 2 OH (25)














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H2O2 + h rarr 2 OH (33)



















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Gas phase

Receptor phase

R1

2

VOC






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(N= 50 SD = 0579 R2 = 0773 F = 287) (34)


(35)


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Solvent c E s a b l

Methanol -0039 -0338 1317 3826 1396 0773

Ethanol 0017 -0232 0867 3894 1192 0846

Propan-1-ol -0042 -0246 0749 3888 1076 0874

Butan-1-ol -0004 -0285 0768 3705 0879 0890

Pentan-1-ol -0002 -0161 0535 3778 0960 0900

Hexan-1-ol -0014 -0205 0583 3621 0891 0913

Heptan-1-ol -0056 -0216 0554 3596 0803 0933

Octan-1-ol -0147 -0214 0561 3507 0749 0943

Octan-1-ol (wet) -0198 0002 0709 3519 1429 0858

Ethylene glycol -0887 0132 1657 4457 2355 0565

Water -1271 0822 2743 3904 4814 -0213





Formamide -0800 0310 2292 4130 1933 0442

Diethylether 0288 -0347 0775 2985 0000 0973

Ethyl acetate 0182 -0352 1316 2891 0000 0916

Propanone 0127 -0387 1733 3060 0000 0866



DMSO -0556 -0223 2903 5037 0000 0719



wwwintechopencom



(N = 47 SD = 0312 R2 = 0901 F = 450) (36)





N

Lo

g (

1N

PT

)

1086420

-1

-2

-3

-4

-5

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(N = 37 SD = 0320 R2 = 0951 F = 1559) (37)


(N = 54 SD = 0338 R2 = 0924 F = 14969) (38)


(N = 91 SD = 0433 R2 = 0936 F = 2045) (39)


wwwintechopencom



(N = 39 SD = 0103 R2 = 0980) (40)


(N = 45 SD = 0140 R2 = 0962 F = 350) (41)



(N = 58 SD = 0354 R2 = 0840 F = 945) (42)

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(43)


(44)



(N = 148 SD = 0192 R2 = 0985 F = 18561) (45)

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(N = 44 SD = 0167 R2 = 0978 F = 3442) (46)




N

Y

1086420

40

30

20

10

0

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N

Y

1086420

30

25

20

15

10

5

0




(N = 643 SD = 0357 R2 = 0992 F = 60830)

(47)


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(48)



Total Outliers














Total 720 77


7 References



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Phone +86-21-62489820 Fax +86-21-62489821












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C 1635

N 1439

O 1243

Si 2683 P 2487 S 2291

Ge 3102 As 2942 Se 2781

Sn 3935 Sb 3774 Te 3614

Pb 4344 Bi 4219

H 871 He 676 B 1832

F 1048 Ne 851 Hg 3400

Cl 2095 Ar 1900

Br 2621 Kr 2460

I 3453 Xe 3290

Rn 3840



wwwintechopencom
























L = ndash 0882 + 1183 E + 0839 S + 0454 A + 0157 B + 3505 V (7)

(N = 4785 SD = 031 R2 = 0992 F = 115279)








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treatments














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(N= 196 SD = 0276 R2 = 0953 F = 7794) (11)


(12)


(13)


(14)


(15)

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(16)


(17)












(18)


(19)


(20)


(21)


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H2O2 + h ------gt 2 OH (25)














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H2O2 + h rarr 2 OH (33)



















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Gas phase

Receptor phase

R1

2

VOC






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(N= 50 SD = 0579 R2 = 0773 F = 287) (34)


(35)


wwwintechopencom


Solvent c E s a b l

Methanol -0039 -0338 1317 3826 1396 0773

Ethanol 0017 -0232 0867 3894 1192 0846

Propan-1-ol -0042 -0246 0749 3888 1076 0874

Butan-1-ol -0004 -0285 0768 3705 0879 0890

Pentan-1-ol -0002 -0161 0535 3778 0960 0900

Hexan-1-ol -0014 -0205 0583 3621 0891 0913

Heptan-1-ol -0056 -0216 0554 3596 0803 0933

Octan-1-ol -0147 -0214 0561 3507 0749 0943

Octan-1-ol (wet) -0198 0002 0709 3519 1429 0858

Ethylene glycol -0887 0132 1657 4457 2355 0565

Water -1271 0822 2743 3904 4814 -0213





Formamide -0800 0310 2292 4130 1933 0442

Diethylether 0288 -0347 0775 2985 0000 0973

Ethyl acetate 0182 -0352 1316 2891 0000 0916

Propanone 0127 -0387 1733 3060 0000 0866



DMSO -0556 -0223 2903 5037 0000 0719



wwwintechopencom



(N = 47 SD = 0312 R2 = 0901 F = 450) (36)





N

Lo

g (

1N

PT

)

1086420

-1

-2

-3

-4

-5

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(N = 37 SD = 0320 R2 = 0951 F = 1559) (37)


(N = 54 SD = 0338 R2 = 0924 F = 14969) (38)


(N = 91 SD = 0433 R2 = 0936 F = 2045) (39)


wwwintechopencom



(N = 39 SD = 0103 R2 = 0980) (40)


(N = 45 SD = 0140 R2 = 0962 F = 350) (41)



(N = 58 SD = 0354 R2 = 0840 F = 945) (42)

wwwintechopencom



(43)


(44)



(N = 148 SD = 0192 R2 = 0985 F = 18561) (45)

wwwintechopencom



(N = 44 SD = 0167 R2 = 0978 F = 3442) (46)




N

Y

1086420

40

30

20

10

0

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N

Y

1086420

30

25

20

15

10

5

0




(N = 643 SD = 0357 R2 = 0992 F = 60830)

(47)


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(48)



Total Outliers














Total 720 77


7 References



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Phone +86-21-62489820 Fax +86-21-62489821







wwwintechopencom





C 1635

N 1439

O 1243

Si 2683 P 2487 S 2291

Ge 3102 As 2942 Se 2781

Sn 3935 Sb 3774 Te 3614

Pb 4344 Bi 4219

H 871 He 676 B 1832

F 1048 Ne 851 Hg 3400

Cl 2095 Ar 1900

Br 2621 Kr 2460

I 3453 Xe 3290

Rn 3840



wwwintechopencom
























L = ndash 0882 + 1183 E + 0839 S + 0454 A + 0157 B + 3505 V (7)

(N = 4785 SD = 031 R2 = 0992 F = 115279)








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treatments














wwwintechopencom





























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(N= 196 SD = 0276 R2 = 0953 F = 7794) (11)


(12)


(13)


(14)


(15)

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(16)


(17)












(18)


(19)


(20)


(21)


wwwintechopencom











wwwintechopencom














wwwintechopencom





wwwintechopencom


H2O2 + h ------gt 2 OH (25)














wwwintechopencom


H2O2 + h rarr 2 OH (33)



















wwwintechopencom



Gas phase

Receptor phase

R1

2

VOC






wwwintechopencom








(N= 50 SD = 0579 R2 = 0773 F = 287) (34)


(35)


wwwintechopencom


Solvent c E s a b l

Methanol -0039 -0338 1317 3826 1396 0773

Ethanol 0017 -0232 0867 3894 1192 0846

Propan-1-ol -0042 -0246 0749 3888 1076 0874

Butan-1-ol -0004 -0285 0768 3705 0879 0890

Pentan-1-ol -0002 -0161 0535 3778 0960 0900

Hexan-1-ol -0014 -0205 0583 3621 0891 0913

Heptan-1-ol -0056 -0216 0554 3596 0803 0933

Octan-1-ol -0147 -0214 0561 3507 0749 0943

Octan-1-ol (wet) -0198 0002 0709 3519 1429 0858

Ethylene glycol -0887 0132 1657 4457 2355 0565

Water -1271 0822 2743 3904 4814 -0213





Formamide -0800 0310 2292 4130 1933 0442

Diethylether 0288 -0347 0775 2985 0000 0973

Ethyl acetate 0182 -0352 1316 2891 0000 0916

Propanone 0127 -0387 1733 3060 0000 0866



DMSO -0556 -0223 2903 5037 0000 0719



wwwintechopencom



(N = 47 SD = 0312 R2 = 0901 F = 450) (36)





N

Lo

g (

1N

PT

)

1086420

-1

-2

-3

-4

-5

wwwintechopencom




(N = 37 SD = 0320 R2 = 0951 F = 1559) (37)


(N = 54 SD = 0338 R2 = 0924 F = 14969) (38)


(N = 91 SD = 0433 R2 = 0936 F = 2045) (39)


wwwintechopencom



(N = 39 SD = 0103 R2 = 0980) (40)


(N = 45 SD = 0140 R2 = 0962 F = 350) (41)



(N = 58 SD = 0354 R2 = 0840 F = 945) (42)

wwwintechopencom



(43)


(44)



(N = 148 SD = 0192 R2 = 0985 F = 18561) (45)

wwwintechopencom



(N = 44 SD = 0167 R2 = 0978 F = 3442) (46)




N

Y

1086420

40

30

20

10

0

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N

Y

1086420

30

25

20

15

10

5

0




(N = 643 SD = 0357 R2 = 0992 F = 60830)

(47)


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(48)



Total Outliers














Total 720 77


7 References



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Phone +86-21-62489820 Fax +86-21-62489821








C 1635

N 1439

O 1243

Si 2683 P 2487 S 2291

Ge 3102 As 2942 Se 2781

Sn 3935 Sb 3774 Te 3614

Pb 4344 Bi 4219

H 871 He 676 B 1832

F 1048 Ne 851 Hg 3400

Cl 2095 Ar 1900

Br 2621 Kr 2460

I 3453 Xe 3290

Rn 3840



wwwintechopencom
























L = ndash 0882 + 1183 E + 0839 S + 0454 A + 0157 B + 3505 V (7)

(N = 4785 SD = 031 R2 = 0992 F = 115279)








wwwintechopencom



treatments














wwwintechopencom





























wwwintechopencom





































wwwintechopencom





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(N= 196 SD = 0276 R2 = 0953 F = 7794) (11)


(12)


(13)


(14)


(15)

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(16)


(17)












(18)


(19)


(20)


(21)


wwwintechopencom











wwwintechopencom














wwwintechopencom





wwwintechopencom


H2O2 + h ------gt 2 OH (25)














wwwintechopencom


H2O2 + h rarr 2 OH (33)



















wwwintechopencom



Gas phase

Receptor phase

R1

2

VOC






wwwintechopencom








(N= 50 SD = 0579 R2 = 0773 F = 287) (34)


(35)


wwwintechopencom


Solvent c E s a b l

Methanol -0039 -0338 1317 3826 1396 0773

Ethanol 0017 -0232 0867 3894 1192 0846

Propan-1-ol -0042 -0246 0749 3888 1076 0874

Butan-1-ol -0004 -0285 0768 3705 0879 0890

Pentan-1-ol -0002 -0161 0535 3778 0960 0900

Hexan-1-ol -0014 -0205 0583 3621 0891 0913

Heptan-1-ol -0056 -0216 0554 3596 0803 0933

Octan-1-ol -0147 -0214 0561 3507 0749 0943

Octan-1-ol (wet) -0198 0002 0709 3519 1429 0858

Ethylene glycol -0887 0132 1657 4457 2355 0565

Water -1271 0822 2743 3904 4814 -0213





Formamide -0800 0310 2292 4130 1933 0442

Diethylether 0288 -0347 0775 2985 0000 0973

Ethyl acetate 0182 -0352 1316 2891 0000 0916

Propanone 0127 -0387 1733 3060 0000 0866



DMSO -0556 -0223 2903 5037 0000 0719



wwwintechopencom



(N = 47 SD = 0312 R2 = 0901 F = 450) (36)





N

Lo

g (

1N

PT

)

1086420

-1

-2

-3

-4

-5

wwwintechopencom




(N = 37 SD = 0320 R2 = 0951 F = 1559) (37)


(N = 54 SD = 0338 R2 = 0924 F = 14969) (38)


(N = 91 SD = 0433 R2 = 0936 F = 2045) (39)


wwwintechopencom



(N = 39 SD = 0103 R2 = 0980) (40)


(N = 45 SD = 0140 R2 = 0962 F = 350) (41)



(N = 58 SD = 0354 R2 = 0840 F = 945) (42)

wwwintechopencom



(43)


(44)



(N = 148 SD = 0192 R2 = 0985 F = 18561) (45)

wwwintechopencom



(N = 44 SD = 0167 R2 = 0978 F = 3442) (46)




N

Y

1086420

40

30

20

10

0

wwwintechopencom



N

Y

1086420

30

25

20

15

10

5

0




(N = 643 SD = 0357 R2 = 0992 F = 60830)

(47)


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(48)



Total Outliers














Total 720 77


7 References



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Phone +86-21-62489820 Fax +86-21-62489821



























L = ndash 0882 + 1183 E + 0839 S + 0454 A + 0157 B + 3505 V (7)

(N = 4785 SD = 031 R2 = 0992 F = 115279)








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treatments














wwwintechopencom





























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(N= 196 SD = 0276 R2 = 0953 F = 7794) (11)


(12)


(13)


(14)


(15)

wwwintechopencom



(16)


(17)












(18)


(19)


(20)


(21)


wwwintechopencom











wwwintechopencom














wwwintechopencom





wwwintechopencom


H2O2 + h ------gt 2 OH (25)














wwwintechopencom


H2O2 + h rarr 2 OH (33)



















wwwintechopencom



Gas phase

Receptor phase

R1

2

VOC






wwwintechopencom








(N= 50 SD = 0579 R2 = 0773 F = 287) (34)


(35)


wwwintechopencom


Solvent c E s a b l

Methanol -0039 -0338 1317 3826 1396 0773

Ethanol 0017 -0232 0867 3894 1192 0846

Propan-1-ol -0042 -0246 0749 3888 1076 0874

Butan-1-ol -0004 -0285 0768 3705 0879 0890

Pentan-1-ol -0002 -0161 0535 3778 0960 0900

Hexan-1-ol -0014 -0205 0583 3621 0891 0913

Heptan-1-ol -0056 -0216 0554 3596 0803 0933

Octan-1-ol -0147 -0214 0561 3507 0749 0943

Octan-1-ol (wet) -0198 0002 0709 3519 1429 0858

Ethylene glycol -0887 0132 1657 4457 2355 0565

Water -1271 0822 2743 3904 4814 -0213





Formamide -0800 0310 2292 4130 1933 0442

Diethylether 0288 -0347 0775 2985 0000 0973

Ethyl acetate 0182 -0352 1316 2891 0000 0916

Propanone 0127 -0387 1733 3060 0000 0866



DMSO -0556 -0223 2903 5037 0000 0719



wwwintechopencom



(N = 47 SD = 0312 R2 = 0901 F = 450) (36)





N

Lo

g (

1N

PT

)

1086420

-1

-2

-3

-4

-5

wwwintechopencom




(N = 37 SD = 0320 R2 = 0951 F = 1559) (37)


(N = 54 SD = 0338 R2 = 0924 F = 14969) (38)


(N = 91 SD = 0433 R2 = 0936 F = 2045) (39)


wwwintechopencom



(N = 39 SD = 0103 R2 = 0980) (40)


(N = 45 SD = 0140 R2 = 0962 F = 350) (41)



(N = 58 SD = 0354 R2 = 0840 F = 945) (42)

wwwintechopencom



(43)


(44)



(N = 148 SD = 0192 R2 = 0985 F = 18561) (45)

wwwintechopencom



(N = 44 SD = 0167 R2 = 0978 F = 3442) (46)




N

Y

1086420

40

30

20

10

0

wwwintechopencom



N

Y

1086420

30

25

20

15

10

5

0




(N = 643 SD = 0357 R2 = 0992 F = 60830)

(47)


wwwintechopencom



(48)



Total Outliers














Total 720 77


7 References



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Phone +86-21-62489820 Fax +86-21-62489821






treatments














wwwintechopencom





























wwwintechopencom





































wwwintechopencom





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(N= 196 SD = 0276 R2 = 0953 F = 7794) (11)


(12)


(13)


(14)


(15)

wwwintechopencom



(16)


(17)












(18)


(19)


(20)


(21)


wwwintechopencom











wwwintechopencom














wwwintechopencom





wwwintechopencom


H2O2 + h ------gt 2 OH (25)














wwwintechopencom


H2O2 + h rarr 2 OH (33)



















wwwintechopencom



Gas phase

Receptor phase

R1

2

VOC






wwwintechopencom








(N= 50 SD = 0579 R2 = 0773 F = 287) (34)


(35)


wwwintechopencom


Solvent c E s a b l

Methanol -0039 -0338 1317 3826 1396 0773

Ethanol 0017 -0232 0867 3894 1192 0846

Propan-1-ol -0042 -0246 0749 3888 1076 0874

Butan-1-ol -0004 -0285 0768 3705 0879 0890

Pentan-1-ol -0002 -0161 0535 3778 0960 0900

Hexan-1-ol -0014 -0205 0583 3621 0891 0913

Heptan-1-ol -0056 -0216 0554 3596 0803 0933

Octan-1-ol -0147 -0214 0561 3507 0749 0943

Octan-1-ol (wet) -0198 0002 0709 3519 1429 0858

Ethylene glycol -0887 0132 1657 4457 2355 0565

Water -1271 0822 2743 3904 4814 -0213





Formamide -0800 0310 2292 4130 1933 0442

Diethylether 0288 -0347 0775 2985 0000 0973

Ethyl acetate 0182 -0352 1316 2891 0000 0916

Propanone 0127 -0387 1733 3060 0000 0866



DMSO -0556 -0223 2903 5037 0000 0719



wwwintechopencom



(N = 47 SD = 0312 R2 = 0901 F = 450) (36)





N

Lo

g (

1N

PT

)

1086420

-1

-2

-3

-4

-5

wwwintechopencom




(N = 37 SD = 0320 R2 = 0951 F = 1559) (37)


(N = 54 SD = 0338 R2 = 0924 F = 14969) (38)


(N = 91 SD = 0433 R2 = 0936 F = 2045) (39)


wwwintechopencom



(N = 39 SD = 0103 R2 = 0980) (40)


(N = 45 SD = 0140 R2 = 0962 F = 350) (41)



(N = 58 SD = 0354 R2 = 0840 F = 945) (42)

wwwintechopencom



(43)


(44)



(N = 148 SD = 0192 R2 = 0985 F = 18561) (45)

wwwintechopencom



(N = 44 SD = 0167 R2 = 0978 F = 3442) (46)




N

Y

1086420

40

30

20

10

0

wwwintechopencom



N

Y

1086420

30

25

20

15

10

5

0




(N = 643 SD = 0357 R2 = 0992 F = 60830)

(47)


wwwintechopencom



(48)



Total Outliers














Total 720 77


7 References



wwwintechopencom


















wwwintechopencom


















wwwintechopencom


















wwwintechopencom
















wwwintechopencom


















wwwintechopencom

















wwwintechopencom

















wwwintechopencom
















wwwintechopencom











wwwintechopencom





Phone +86-21-62489820 Fax +86-21-62489821
































wwwintechopencom





































wwwintechopencom





wwwintechopencom



(N= 196 SD = 0276 R2 = 0953 F = 7794) (11)


(12)


(13)


(14)


(15)

wwwintechopencom



(16)


(17)












(18)


(19)


(20)


(21)


wwwintechopencom











wwwintechopencom














wwwintechopencom





wwwintechopencom


H2O2 + h ------gt 2 OH (25)














wwwintechopencom


H2O2 + h rarr 2 OH (33)



















wwwintechopencom



Gas phase

Receptor phase

R1

2

VOC






wwwintechopencom








(N= 50 SD = 0579 R2 = 0773 F = 287) (34)


(35)


wwwintechopencom


Solvent c E s a b l

Methanol -0039 -0338 1317 3826 1396 0773

Ethanol 0017 -0232 0867 3894 1192 0846

Propan-1-ol -0042 -0246 0749 3888 1076 0874

Butan-1-ol -0004 -0285 0768 3705 0879 0890

Pentan-1-ol -0002 -0161 0535 3778 0960 0900

Hexan-1-ol -0014 -0205 0583 3621 0891 0913

Heptan-1-ol -0056 -0216 0554 3596 0803 0933

Octan-1-ol -0147 -0214 0561 3507 0749 0943

Octan-1-ol (wet) -0198 0002 0709 3519 1429 0858

Ethylene glycol -0887 0132 1657 4457 2355 0565

Water -1271 0822 2743 3904 4814 -0213





Formamide -0800 0310 2292 4130 1933 0442

Diethylether 0288 -0347 0775 2985 0000 0973

Ethyl acetate 0182 -0352 1316 2891 0000 0916

Propanone 0127 -0387 1733 3060 0000 0866



DMSO -0556 -0223 2903 5037 0000 0719



wwwintechopencom



(N = 47 SD = 0312 R2 = 0901 F = 450) (36)





N

Lo

g (

1N

PT

)

1086420

-1

-2

-3

-4

-5

wwwintechopencom




(N = 37 SD = 0320 R2 = 0951 F = 1559) (37)


(N = 54 SD = 0338 R2 = 0924 F = 14969) (38)


(N = 91 SD = 0433 R2 = 0936 F = 2045) (39)


wwwintechopencom



(N = 39 SD = 0103 R2 = 0980) (40)


(N = 45 SD = 0140 R2 = 0962 F = 350) (41)



(N = 58 SD = 0354 R2 = 0840 F = 945) (42)

wwwintechopencom



(43)


(44)



(N = 148 SD = 0192 R2 = 0985 F = 18561) (45)

wwwintechopencom



(N = 44 SD = 0167 R2 = 0978 F = 3442) (46)




N

Y

1086420

40

30

20

10

0

wwwintechopencom



N

Y

1086420

30

25

20

15

10

5

0




(N = 643 SD = 0357 R2 = 0992 F = 60830)

(47)


wwwintechopencom



(48)



Total Outliers














Total 720 77


7 References



wwwintechopencom


















wwwintechopencom


















wwwintechopencom


















wwwintechopencom
















wwwintechopencom


















wwwintechopencom

















wwwintechopencom

















wwwintechopencom
















wwwintechopencom











wwwintechopencom





Phone +86-21-62489820 Fax +86-21-62489821








































wwwintechopencom





wwwintechopencom



(N= 196 SD = 0276 R2 = 0953 F = 7794) (11)


(12)


(13)


(14)


(15)

wwwintechopencom



(16)


(17)












(18)


(19)


(20)


(21)


wwwintechopencom











wwwintechopencom














wwwintechopencom





wwwintechopencom


H2O2 + h ------gt 2 OH (25)














wwwintechopencom


H2O2 + h rarr 2 OH (33)



















wwwintechopencom



Gas phase

Receptor phase

R1

2

VOC






wwwintechopencom








(N= 50 SD = 0579 R2 = 0773 F = 287) (34)


(35)


wwwintechopencom


Solvent c E s a b l

Methanol -0039 -0338 1317 3826 1396 0773

Ethanol 0017 -0232 0867 3894 1192 0846

Propan-1-ol -0042 -0246 0749 3888 1076 0874

Butan-1-ol -0004 -0285 0768 3705 0879 0890

Pentan-1-ol -0002 -0161 0535 3778 0960 0900

Hexan-1-ol -0014 -0205 0583 3621 0891 0913

Heptan-1-ol -0056 -0216 0554 3596 0803 0933

Octan-1-ol -0147 -0214 0561 3507 0749 0943

Octan-1-ol (wet) -0198 0002 0709 3519 1429 0858

Ethylene glycol -0887 0132 1657 4457 2355 0565

Water -1271 0822 2743 3904 4814 -0213





Formamide -0800 0310 2292 4130 1933 0442

Diethylether 0288 -0347 0775 2985 0000 0973

Ethyl acetate 0182 -0352 1316 2891 0000 0916

Propanone 0127 -0387 1733 3060 0000 0866



DMSO -0556 -0223 2903 5037 0000 0719



wwwintechopencom



(N = 47 SD = 0312 R2 = 0901 F = 450) (36)





N

Lo

g (

1N

PT

)

1086420

-1

-2

-3

-4

-5

wwwintechopencom




(N = 37 SD = 0320 R2 = 0951 F = 1559) (37)


(N = 54 SD = 0338 R2 = 0924 F = 14969) (38)


(N = 91 SD = 0433 R2 = 0936 F = 2045) (39)


wwwintechopencom



(N = 39 SD = 0103 R2 = 0980) (40)


(N = 45 SD = 0140 R2 = 0962 F = 350) (41)



(N = 58 SD = 0354 R2 = 0840 F = 945) (42)

wwwintechopencom



(43)


(44)



(N = 148 SD = 0192 R2 = 0985 F = 18561) (45)

wwwintechopencom



(N = 44 SD = 0167 R2 = 0978 F = 3442) (46)




N

Y

1086420

40

30

20

10

0

wwwintechopencom



N

Y

1086420

30

25

20

15

10

5

0




(N = 643 SD = 0357 R2 = 0992 F = 60830)

(47)


wwwintechopencom



(48)



Total Outliers














Total 720 77


7 References



wwwintechopencom


















wwwintechopencom


















wwwintechopencom


















wwwintechopencom
















wwwintechopencom


















wwwintechopencom

















wwwintechopencom

















wwwintechopencom
















wwwintechopencom











wwwintechopencom





Phone +86-21-62489820 Fax +86-21-62489821








wwwintechopencom



(N= 196 SD = 0276 R2 = 0953 F = 7794) (11)


(12)


(13)


(14)


(15)

wwwintechopencom



(16)


(17)












(18)


(19)


(20)


(21)


wwwintechopencom











wwwintechopencom














wwwintechopencom





wwwintechopencom


H2O2 + h ------gt 2 OH (25)














wwwintechopencom


H2O2 + h rarr 2 OH (33)



















wwwintechopencom



Gas phase

Receptor phase

R1

2

VOC






wwwintechopencom








(N= 50 SD = 0579 R2 = 0773 F = 287) (34)


(35)


wwwintechopencom


Solvent c E s a b l

Methanol -0039 -0338 1317 3826 1396 0773

Ethanol 0017 -0232 0867 3894 1192 0846

Propan-1-ol -0042 -0246 0749 3888 1076 0874

Butan-1-ol -0004 -0285 0768 3705 0879 0890

Pentan-1-ol -0002 -0161 0535 3778 0960 0900

Hexan-1-ol -0014 -0205 0583 3621 0891 0913

Heptan-1-ol -0056 -0216 0554 3596 0803 0933

Octan-1-ol -0147 -0214 0561 3507 0749 0943

Octan-1-ol (wet) -0198 0002 0709 3519 1429 0858

Ethylene glycol -0887 0132 1657 4457 2355 0565

Water -1271 0822 2743 3904 4814 -0213





Formamide -0800 0310 2292 4130 1933 0442

Diethylether 0288 -0347 0775 2985 0000 0973

Ethyl acetate 0182 -0352 1316 2891 0000 0916

Propanone 0127 -0387 1733 3060 0000 0866



DMSO -0556 -0223 2903 5037 0000 0719



wwwintechopencom



(N = 47 SD = 0312 R2 = 0901 F = 450) (36)





N

Lo

g (

1N

PT

)

1086420

-1

-2

-3

-4

-5

wwwintechopencom




(N = 37 SD = 0320 R2 = 0951 F = 1559) (37)


(N = 54 SD = 0338 R2 = 0924 F = 14969) (38)


(N = 91 SD = 0433 R2 = 0936 F = 2045) (39)


wwwintechopencom



(N = 39 SD = 0103 R2 = 0980) (40)


(N = 45 SD = 0140 R2 = 0962 F = 350) (41)



(N = 58 SD = 0354 R2 = 0840 F = 945) (42)

wwwintechopencom



(43)


(44)



(N = 148 SD = 0192 R2 = 0985 F = 18561) (45)

wwwintechopencom



(N = 44 SD = 0167 R2 = 0978 F = 3442) (46)




N

Y

1086420

40

30

20

10

0

wwwintechopencom



N

Y

1086420

30

25

20

15

10

5

0




(N = 643 SD = 0357 R2 = 0992 F = 60830)

(47)


wwwintechopencom



(48)



Total Outliers














Total 720 77


7 References



wwwintechopencom


















wwwintechopencom


















wwwintechopencom


















wwwintechopencom
















wwwintechopencom


















wwwintechopencom

















wwwintechopencom

















wwwintechopencom
















wwwintechopencom











wwwintechopencom





Phone +86-21-62489820 Fax +86-21-62489821






(N= 196 SD = 0276 R2 = 0953 F = 7794) (11)


(12)


(13)


(14)


(15)

wwwintechopencom



(16)


(17)












(18)


(19)


(20)


(21)


wwwintechopencom











wwwintechopencom














wwwintechopencom





wwwintechopencom


H2O2 + h ------gt 2 OH (25)














wwwintechopencom


H2O2 + h rarr 2 OH (33)



















wwwintechopencom



Gas phase

Receptor phase

R1

2

VOC






wwwintechopencom








(N= 50 SD = 0579 R2 = 0773 F = 287) (34)


(35)


wwwintechopencom


Solvent c E s a b l

Methanol -0039 -0338 1317 3826 1396 0773

Ethanol 0017 -0232 0867 3894 1192 0846

Propan-1-ol -0042 -0246 0749 3888 1076 0874

Butan-1-ol -0004 -0285 0768 3705 0879 0890

Pentan-1-ol -0002 -0161 0535 3778 0960 0900

Hexan-1-ol -0014 -0205 0583 3621 0891 0913

Heptan-1-ol -0056 -0216 0554 3596 0803 0933

Octan-1-ol -0147 -0214 0561 3507 0749 0943

Octan-1-ol (wet) -0198 0002 0709 3519 1429 0858

Ethylene glycol -0887 0132 1657 4457 2355 0565

Water -1271 0822 2743 3904 4814 -0213





Formamide -0800 0310 2292 4130 1933 0442

Diethylether 0288 -0347 0775 2985 0000 0973

Ethyl acetate 0182 -0352 1316 2891 0000 0916

Propanone 0127 -0387 1733 3060 0000 0866



DMSO -0556 -0223 2903 5037 0000 0719



wwwintechopencom



(N = 47 SD = 0312 R2 = 0901 F = 450) (36)





N

Lo

g (

1N

PT

)

1086420

-1

-2

-3

-4

-5

wwwintechopencom




(N = 37 SD = 0320 R2 = 0951 F = 1559) (37)


(N = 54 SD = 0338 R2 = 0924 F = 14969) (38)


(N = 91 SD = 0433 R2 = 0936 F = 2045) (39)


wwwintechopencom



(N = 39 SD = 0103 R2 = 0980) (40)


(N = 45 SD = 0140 R2 = 0962 F = 350) (41)



(N = 58 SD = 0354 R2 = 0840 F = 945) (42)

wwwintechopencom



(43)


(44)



(N = 148 SD = 0192 R2 = 0985 F = 18561) (45)

wwwintechopencom



(N = 44 SD = 0167 R2 = 0978 F = 3442) (46)




N

Y

1086420

40

30

20

10

0

wwwintechopencom



N

Y

1086420

30

25

20

15

10

5

0




(N = 643 SD = 0357 R2 = 0992 F = 60830)

(47)


wwwintechopencom



(48)



Total Outliers














Total 720 77


7 References



wwwintechopencom


















wwwintechopencom


















wwwintechopencom


















wwwintechopencom
















wwwintechopencom


















wwwintechopencom

















wwwintechopencom

















wwwintechopencom
















wwwintechopencom











wwwintechopencom





Phone +86-21-62489820 Fax +86-21-62489821






(16)


(17)












(18)


(19)


(20)


(21)


wwwintechopencom











wwwintechopencom














wwwintechopencom





wwwintechopencom


H2O2 + h ------gt 2 OH (25)














wwwintechopencom


H2O2 + h rarr 2 OH (33)



















wwwintechopencom



Gas phase

Receptor phase

R1

2

VOC






wwwintechopencom








(N= 50 SD = 0579 R2 = 0773 F = 287) (34)


(35)


wwwintechopencom


Solvent c E s a b l

Methanol -0039 -0338 1317 3826 1396 0773

Ethanol 0017 -0232 0867 3894 1192 0846

Propan-1-ol -0042 -0246 0749 3888 1076 0874

Butan-1-ol -0004 -0285 0768 3705 0879 0890

Pentan-1-ol -0002 -0161 0535 3778 0960 0900

Hexan-1-ol -0014 -0205 0583 3621 0891 0913

Heptan-1-ol -0056 -0216 0554 3596 0803 0933

Octan-1-ol -0147 -0214 0561 3507 0749 0943

Octan-1-ol (wet) -0198 0002 0709 3519 1429 0858

Ethylene glycol -0887 0132 1657 4457 2355 0565

Water -1271 0822 2743 3904 4814 -0213





Formamide -0800 0310 2292 4130 1933 0442

Diethylether 0288 -0347 0775 2985 0000 0973

Ethyl acetate 0182 -0352 1316 2891 0000 0916

Propanone 0127 -0387 1733 3060 0000 0866



DMSO -0556 -0223 2903 5037 0000 0719



wwwintechopencom



(N = 47 SD = 0312 R2 = 0901 F = 450) (36)





N

Lo

g (

1N

PT

)

1086420

-1

-2

-3

-4

-5

wwwintechopencom




(N = 37 SD = 0320 R2 = 0951 F = 1559) (37)


(N = 54 SD = 0338 R2 = 0924 F = 14969) (38)


(N = 91 SD = 0433 R2 = 0936 F = 2045) (39)


wwwintechopencom



(N = 39 SD = 0103 R2 = 0980) (40)


(N = 45 SD = 0140 R2 = 0962 F = 350) (41)



(N = 58 SD = 0354 R2 = 0840 F = 945) (42)

wwwintechopencom



(43)


(44)



(N = 148 SD = 0192 R2 = 0985 F = 18561) (45)

wwwintechopencom



(N = 44 SD = 0167 R2 = 0978 F = 3442) (46)




N

Y

1086420

40

30

20

10

0

wwwintechopencom



N

Y

1086420

30

25

20

15

10

5

0




(N = 643 SD = 0357 R2 = 0992 F = 60830)

(47)


wwwintechopencom



(48)



Total Outliers














Total 720 77


7 References



wwwintechopencom


















wwwintechopencom


















wwwintechopencom


















wwwintechopencom
















wwwintechopencom


















wwwintechopencom

















wwwintechopencom

















wwwintechopencom
















wwwintechopencom











wwwintechopencom





Phone +86-21-62489820 Fax +86-21-62489821














wwwintechopencom














wwwintechopencom





wwwintechopencom


H2O2 + h ------gt 2 OH (25)














wwwintechopencom


H2O2 + h rarr 2 OH (33)



















wwwintechopencom



Gas phase

Receptor phase

R1

2

VOC






wwwintechopencom








(N= 50 SD = 0579 R2 = 0773 F = 287) (34)


(35)


wwwintechopencom


Solvent c E s a b l

Methanol -0039 -0338 1317 3826 1396 0773

Ethanol 0017 -0232 0867 3894 1192 0846

Propan-1-ol -0042 -0246 0749 3888 1076 0874

Butan-1-ol -0004 -0285 0768 3705 0879 0890

Pentan-1-ol -0002 -0161 0535 3778 0960 0900

Hexan-1-ol -0014 -0205 0583 3621 0891 0913

Heptan-1-ol -0056 -0216 0554 3596 0803 0933

Octan-1-ol -0147 -0214 0561 3507 0749 0943

Octan-1-ol (wet) -0198 0002 0709 3519 1429 0858

Ethylene glycol -0887 0132 1657 4457 2355 0565

Water -1271 0822 2743 3904 4814 -0213





Formamide -0800 0310 2292 4130 1933 0442

Diethylether 0288 -0347 0775 2985 0000 0973

Ethyl acetate 0182 -0352 1316 2891 0000 0916

Propanone 0127 -0387 1733 3060 0000 0866



DMSO -0556 -0223 2903 5037 0000 0719



wwwintechopencom



(N = 47 SD = 0312 R2 = 0901 F = 450) (36)





N

Lo

g (

1N

PT

)

1086420

-1

-2

-3

-4

-5

wwwintechopencom




(N = 37 SD = 0320 R2 = 0951 F = 1559) (37)


(N = 54 SD = 0338 R2 = 0924 F = 14969) (38)


(N = 91 SD = 0433 R2 = 0936 F = 2045) (39)


wwwintechopencom



(N = 39 SD = 0103 R2 = 0980) (40)


(N = 45 SD = 0140 R2 = 0962 F = 350) (41)



(N = 58 SD = 0354 R2 = 0840 F = 945) (42)

wwwintechopencom



(43)


(44)



(N = 148 SD = 0192 R2 = 0985 F = 18561) (45)

wwwintechopencom



(N = 44 SD = 0167 R2 = 0978 F = 3442) (46)




N

Y

1086420

40

30

20

10

0

wwwintechopencom



N

Y

1086420

30

25

20

15

10

5

0




(N = 643 SD = 0357 R2 = 0992 F = 60830)

(47)


wwwintechopencom



(48)



Total Outliers














Total 720 77


7 References



wwwintechopencom


















wwwintechopencom


















wwwintechopencom


















wwwintechopencom
















wwwintechopencom


















wwwintechopencom

















wwwintechopencom

















wwwintechopencom
















wwwintechopencom











wwwintechopencom





Phone +86-21-62489820 Fax +86-21-62489821

















wwwintechopencom





wwwintechopencom


H2O2 + h ------gt 2 OH (25)














wwwintechopencom


H2O2 + h rarr 2 OH (33)



















wwwintechopencom



Gas phase

Receptor phase

R1

2

VOC






wwwintechopencom








(N= 50 SD = 0579 R2 = 0773 F = 287) (34)


(35)


wwwintechopencom


Solvent c E s a b l

Methanol -0039 -0338 1317 3826 1396 0773

Ethanol 0017 -0232 0867 3894 1192 0846

Propan-1-ol -0042 -0246 0749 3888 1076 0874

Butan-1-ol -0004 -0285 0768 3705 0879 0890

Pentan-1-ol -0002 -0161 0535 3778 0960 0900

Hexan-1-ol -0014 -0205 0583 3621 0891 0913

Heptan-1-ol -0056 -0216 0554 3596 0803 0933

Octan-1-ol -0147 -0214 0561 3507 0749 0943

Octan-1-ol (wet) -0198 0002 0709 3519 1429 0858

Ethylene glycol -0887 0132 1657 4457 2355 0565

Water -1271 0822 2743 3904 4814 -0213





Formamide -0800 0310 2292 4130 1933 0442

Diethylether 0288 -0347 0775 2985 0000 0973

Ethyl acetate 0182 -0352 1316 2891 0000 0916

Propanone 0127 -0387 1733 3060 0000 0866



DMSO -0556 -0223 2903 5037 0000 0719



wwwintechopencom



(N = 47 SD = 0312 R2 = 0901 F = 450) (36)





N

Lo

g (

1N

PT

)

1086420

-1

-2

-3

-4

-5

wwwintechopencom




(N = 37 SD = 0320 R2 = 0951 F = 1559) (37)


(N = 54 SD = 0338 R2 = 0924 F = 14969) (38)


(N = 91 SD = 0433 R2 = 0936 F = 2045) (39)


wwwintechopencom



(N = 39 SD = 0103 R2 = 0980) (40)


(N = 45 SD = 0140 R2 = 0962 F = 350) (41)



(N = 58 SD = 0354 R2 = 0840 F = 945) (42)

wwwintechopencom



(43)


(44)



(N = 148 SD = 0192 R2 = 0985 F = 18561) (45)

wwwintechopencom



(N = 44 SD = 0167 R2 = 0978 F = 3442) (46)




N

Y

1086420

40

30

20

10

0

wwwintechopencom



N

Y

1086420

30

25

20

15

10

5

0




(N = 643 SD = 0357 R2 = 0992 F = 60830)

(47)


wwwintechopencom



(48)



Total Outliers














Total 720 77


7 References



wwwintechopencom


















wwwintechopencom


















wwwintechopencom


















wwwintechopencom
















wwwintechopencom


















wwwintechopencom

















wwwintechopencom

















wwwintechopencom
















wwwintechopencom











wwwintechopencom





Phone +86-21-62489820 Fax +86-21-62489821








wwwintechopencom


H2O2 + h ------gt 2 OH (25)














wwwintechopencom


H2O2 + h rarr 2 OH (33)



















wwwintechopencom



Gas phase

Receptor phase

R1

2

VOC






wwwintechopencom








(N= 50 SD = 0579 R2 = 0773 F = 287) (34)


(35)


wwwintechopencom


Solvent c E s a b l

Methanol -0039 -0338 1317 3826 1396 0773

Ethanol 0017 -0232 0867 3894 1192 0846

Propan-1-ol -0042 -0246 0749 3888 1076 0874

Butan-1-ol -0004 -0285 0768 3705 0879 0890

Pentan-1-ol -0002 -0161 0535 3778 0960 0900

Hexan-1-ol -0014 -0205 0583 3621 0891 0913

Heptan-1-ol -0056 -0216 0554 3596 0803 0933

Octan-1-ol -0147 -0214 0561 3507 0749 0943

Octan-1-ol (wet) -0198 0002 0709 3519 1429 0858

Ethylene glycol -0887 0132 1657 4457 2355 0565

Water -1271 0822 2743 3904 4814 -0213





Formamide -0800 0310 2292 4130 1933 0442

Diethylether 0288 -0347 0775 2985 0000 0973

Ethyl acetate 0182 -0352 1316 2891 0000 0916

Propanone 0127 -0387 1733 3060 0000 0866



DMSO -0556 -0223 2903 5037 0000 0719



wwwintechopencom



(N = 47 SD = 0312 R2 = 0901 F = 450) (36)





N

Lo

g (

1N

PT

)

1086420

-1

-2

-3

-4

-5

wwwintechopencom




(N = 37 SD = 0320 R2 = 0951 F = 1559) (37)


(N = 54 SD = 0338 R2 = 0924 F = 14969) (38)


(N = 91 SD = 0433 R2 = 0936 F = 2045) (39)


wwwintechopencom



(N = 39 SD = 0103 R2 = 0980) (40)


(N = 45 SD = 0140 R2 = 0962 F = 350) (41)



(N = 58 SD = 0354 R2 = 0840 F = 945) (42)

wwwintechopencom



(43)


(44)



(N = 148 SD = 0192 R2 = 0985 F = 18561) (45)

wwwintechopencom



(N = 44 SD = 0167 R2 = 0978 F = 3442) (46)




N

Y

1086420

40

30

20

10

0

wwwintechopencom



N

Y

1086420

30

25

20

15

10

5

0




(N = 643 SD = 0357 R2 = 0992 F = 60830)

(47)


wwwintechopencom



(48)



Total Outliers














Total 720 77


7 References



wwwintechopencom


















wwwintechopencom


















wwwintechopencom


















wwwintechopencom
















wwwintechopencom


















wwwintechopencom

















wwwintechopencom

















wwwintechopencom
















wwwintechopencom











wwwintechopencom





Phone +86-21-62489820 Fax +86-21-62489821





H2O2 + h ------gt 2 OH (25)














wwwintechopencom


H2O2 + h rarr 2 OH (33)



















wwwintechopencom



Gas phase

Receptor phase

R1

2

VOC






wwwintechopencom








(N= 50 SD = 0579 R2 = 0773 F = 287) (34)


(35)


wwwintechopencom


Solvent c E s a b l

Methanol -0039 -0338 1317 3826 1396 0773

Ethanol 0017 -0232 0867 3894 1192 0846

Propan-1-ol -0042 -0246 0749 3888 1076 0874

Butan-1-ol -0004 -0285 0768 3705 0879 0890

Pentan-1-ol -0002 -0161 0535 3778 0960 0900

Hexan-1-ol -0014 -0205 0583 3621 0891 0913

Heptan-1-ol -0056 -0216 0554 3596 0803 0933

Octan-1-ol -0147 -0214 0561 3507 0749 0943

Octan-1-ol (wet) -0198 0002 0709 3519 1429 0858

Ethylene glycol -0887 0132 1657 4457 2355 0565

Water -1271 0822 2743 3904 4814 -0213





Formamide -0800 0310 2292 4130 1933 0442

Diethylether 0288 -0347 0775 2985 0000 0973

Ethyl acetate 0182 -0352 1316 2891 0000 0916

Propanone 0127 -0387 1733 3060 0000 0866



DMSO -0556 -0223 2903 5037 0000 0719



wwwintechopencom



(N = 47 SD = 0312 R2 = 0901 F = 450) (36)





N

Lo

g (

1N

PT

)

1086420

-1

-2

-3

-4

-5

wwwintechopencom




(N = 37 SD = 0320 R2 = 0951 F = 1559) (37)


(N = 54 SD = 0338 R2 = 0924 F = 14969) (38)


(N = 91 SD = 0433 R2 = 0936 F = 2045) (39)


wwwintechopencom



(N = 39 SD = 0103 R2 = 0980) (40)


(N = 45 SD = 0140 R2 = 0962 F = 350) (41)



(N = 58 SD = 0354 R2 = 0840 F = 945) (42)

wwwintechopencom



(43)


(44)



(N = 148 SD = 0192 R2 = 0985 F = 18561) (45)

wwwintechopencom



(N = 44 SD = 0167 R2 = 0978 F = 3442) (46)




N

Y

1086420

40

30

20

10

0

wwwintechopencom



N

Y

1086420

30

25

20

15

10

5

0




(N = 643 SD = 0357 R2 = 0992 F = 60830)

(47)


wwwintechopencom



(48)



Total Outliers














Total 720 77


7 References



wwwintechopencom


















wwwintechopencom


















wwwintechopencom


















wwwintechopencom
















wwwintechopencom


















wwwintechopencom

















wwwintechopencom

















wwwintechopencom
















wwwintechopencom











wwwintechopencom





Phone +86-21-62489820 Fax +86-21-62489821





H2O2 + h rarr 2 OH (33)



















wwwintechopencom



Gas phase

Receptor phase

R1

2

VOC






wwwintechopencom








(N= 50 SD = 0579 R2 = 0773 F = 287) (34)


(35)


wwwintechopencom


Solvent c E s a b l

Methanol -0039 -0338 1317 3826 1396 0773

Ethanol 0017 -0232 0867 3894 1192 0846

Propan-1-ol -0042 -0246 0749 3888 1076 0874

Butan-1-ol -0004 -0285 0768 3705 0879 0890

Pentan-1-ol -0002 -0161 0535 3778 0960 0900

Hexan-1-ol -0014 -0205 0583 3621 0891 0913

Heptan-1-ol -0056 -0216 0554 3596 0803 0933

Octan-1-ol -0147 -0214 0561 3507 0749 0943

Octan-1-ol (wet) -0198 0002 0709 3519 1429 0858

Ethylene glycol -0887 0132 1657 4457 2355 0565

Water -1271 0822 2743 3904 4814 -0213





Formamide -0800 0310 2292 4130 1933 0442

Diethylether 0288 -0347 0775 2985 0000 0973

Ethyl acetate 0182 -0352 1316 2891 0000 0916

Propanone 0127 -0387 1733 3060 0000 0866



DMSO -0556 -0223 2903 5037 0000 0719



wwwintechopencom



(N = 47 SD = 0312 R2 = 0901 F = 450) (36)





N

Lo

g (

1N

PT

)

1086420

-1

-2

-3

-4

-5

wwwintechopencom




(N = 37 SD = 0320 R2 = 0951 F = 1559) (37)


(N = 54 SD = 0338 R2 = 0924 F = 14969) (38)


(N = 91 SD = 0433 R2 = 0936 F = 2045) (39)


wwwintechopencom



(N = 39 SD = 0103 R2 = 0980) (40)


(N = 45 SD = 0140 R2 = 0962 F = 350) (41)



(N = 58 SD = 0354 R2 = 0840 F = 945) (42)

wwwintechopencom



(43)


(44)



(N = 148 SD = 0192 R2 = 0985 F = 18561) (45)

wwwintechopencom



(N = 44 SD = 0167 R2 = 0978 F = 3442) (46)




N

Y

1086420

40

30

20

10

0

wwwintechopencom



N

Y

1086420

30

25

20

15

10

5

0




(N = 643 SD = 0357 R2 = 0992 F = 60830)

(47)


wwwintechopencom



(48)



Total Outliers














Total 720 77


7 References



wwwintechopencom


















wwwintechopencom


















wwwintechopencom


















wwwintechopencom
















wwwintechopencom


















wwwintechopencom

















wwwintechopencom

















wwwintechopencom
















wwwintechopencom











wwwintechopencom





Phone +86-21-62489820 Fax +86-21-62489821






Gas phase

Receptor phase

R1

2

VOC






wwwintechopencom








(N= 50 SD = 0579 R2 = 0773 F = 287) (34)


(35)


wwwintechopencom


Solvent c E s a b l

Methanol -0039 -0338 1317 3826 1396 0773

Ethanol 0017 -0232 0867 3894 1192 0846

Propan-1-ol -0042 -0246 0749 3888 1076 0874

Butan-1-ol -0004 -0285 0768 3705 0879 0890

Pentan-1-ol -0002 -0161 0535 3778 0960 0900

Hexan-1-ol -0014 -0205 0583 3621 0891 0913

Heptan-1-ol -0056 -0216 0554 3596 0803 0933

Octan-1-ol -0147 -0214 0561 3507 0749 0943

Octan-1-ol (wet) -0198 0002 0709 3519 1429 0858

Ethylene glycol -0887 0132 1657 4457 2355 0565

Water -1271 0822 2743 3904 4814 -0213





Formamide -0800 0310 2292 4130 1933 0442

Diethylether 0288 -0347 0775 2985 0000 0973

Ethyl acetate 0182 -0352 1316 2891 0000 0916

Propanone 0127 -0387 1733 3060 0000 0866



DMSO -0556 -0223 2903 5037 0000 0719



wwwintechopencom



(N = 47 SD = 0312 R2 = 0901 F = 450) (36)





N

Lo

g (

1N

PT

)

1086420

-1

-2

-3

-4

-5

wwwintechopencom




(N = 37 SD = 0320 R2 = 0951 F = 1559) (37)


(N = 54 SD = 0338 R2 = 0924 F = 14969) (38)


(N = 91 SD = 0433 R2 = 0936 F = 2045) (39)


wwwintechopencom



(N = 39 SD = 0103 R2 = 0980) (40)


(N = 45 SD = 0140 R2 = 0962 F = 350) (41)



(N = 58 SD = 0354 R2 = 0840 F = 945) (42)

wwwintechopencom



(43)


(44)



(N = 148 SD = 0192 R2 = 0985 F = 18561) (45)

wwwintechopencom



(N = 44 SD = 0167 R2 = 0978 F = 3442) (46)




N

Y

1086420

40

30

20

10

0

wwwintechopencom



N

Y

1086420

30

25

20

15

10

5

0




(N = 643 SD = 0357 R2 = 0992 F = 60830)

(47)


wwwintechopencom



(48)



Total Outliers














Total 720 77


7 References



wwwintechopencom


















wwwintechopencom


















wwwintechopencom


















wwwintechopencom
















wwwintechopencom


















wwwintechopencom

















wwwintechopencom

















wwwintechopencom
















wwwintechopencom











wwwintechopencom





Phone +86-21-62489820 Fax +86-21-62489821











(N= 50 SD = 0579 R2 = 0773 F = 287) (34)


(35)


wwwintechopencom


Solvent c E s a b l

Methanol -0039 -0338 1317 3826 1396 0773

Ethanol 0017 -0232 0867 3894 1192 0846

Propan-1-ol -0042 -0246 0749 3888 1076 0874

Butan-1-ol -0004 -0285 0768 3705 0879 0890

Pentan-1-ol -0002 -0161 0535 3778 0960 0900

Hexan-1-ol -0014 -0205 0583 3621 0891 0913

Heptan-1-ol -0056 -0216 0554 3596 0803 0933

Octan-1-ol -0147 -0214 0561 3507 0749 0943

Octan-1-ol (wet) -0198 0002 0709 3519 1429 0858

Ethylene glycol -0887 0132 1657 4457 2355 0565

Water -1271 0822 2743 3904 4814 -0213





Formamide -0800 0310 2292 4130 1933 0442

Diethylether 0288 -0347 0775 2985 0000 0973

Ethyl acetate 0182 -0352 1316 2891 0000 0916

Propanone 0127 -0387 1733 3060 0000 0866



DMSO -0556 -0223 2903 5037 0000 0719



wwwintechopencom



(N = 47 SD = 0312 R2 = 0901 F = 450) (36)





N

Lo

g (

1N

PT

)

1086420

-1

-2

-3

-4

-5

wwwintechopencom




(N = 37 SD = 0320 R2 = 0951 F = 1559) (37)


(N = 54 SD = 0338 R2 = 0924 F = 14969) (38)


(N = 91 SD = 0433 R2 = 0936 F = 2045) (39)


wwwintechopencom



(N = 39 SD = 0103 R2 = 0980) (40)


(N = 45 SD = 0140 R2 = 0962 F = 350) (41)



(N = 58 SD = 0354 R2 = 0840 F = 945) (42)

wwwintechopencom



(43)


(44)



(N = 148 SD = 0192 R2 = 0985 F = 18561) (45)

wwwintechopencom



(N = 44 SD = 0167 R2 = 0978 F = 3442) (46)




N

Y

1086420

40

30

20

10

0

wwwintechopencom



N

Y

1086420

30

25

20

15

10

5

0




(N = 643 SD = 0357 R2 = 0992 F = 60830)

(47)


wwwintechopencom



(48)



Total Outliers














Total 720 77


7 References



wwwintechopencom


















wwwintechopencom


















wwwintechopencom


















wwwintechopencom
















wwwintechopencom


















wwwintechopencom

















wwwintechopencom

















wwwintechopencom
















wwwintechopencom











wwwintechopencom





Phone +86-21-62489820 Fax +86-21-62489821





Solvent c E s a b l

Methanol -0039 -0338 1317 3826 1396 0773

Ethanol 0017 -0232 0867 3894 1192 0846

Propan-1-ol -0042 -0246 0749 3888 1076 0874

Butan-1-ol -0004 -0285 0768 3705 0879 0890

Pentan-1-ol -0002 -0161 0535 3778 0960 0900

Hexan-1-ol -0014 -0205 0583 3621 0891 0913

Heptan-1-ol -0056 -0216 0554 3596 0803 0933

Octan-1-ol -0147 -0214 0561 3507 0749 0943

Octan-1-ol (wet) -0198 0002 0709 3519 1429 0858

Ethylene glycol -0887 0132 1657 4457 2355 0565

Water -1271 0822 2743 3904 4814 -0213





Formamide -0800 0310 2292 4130 1933 0442

Diethylether 0288 -0347 0775 2985 0000 0973

Ethyl acetate 0182 -0352 1316 2891 0000 0916

Propanone 0127 -0387 1733 3060 0000 0866



DMSO -0556 -0223 2903 5037 0000 0719



wwwintechopencom



(N = 47 SD = 0312 R2 = 0901 F = 450) (36)





N

Lo

g (

1N

PT

)

1086420

-1

-2

-3

-4

-5

wwwintechopencom




(N = 37 SD = 0320 R2 = 0951 F = 1559) (37)


(N = 54 SD = 0338 R2 = 0924 F = 14969) (38)


(N = 91 SD = 0433 R2 = 0936 F = 2045) (39)


wwwintechopencom



(N = 39 SD = 0103 R2 = 0980) (40)


(N = 45 SD = 0140 R2 = 0962 F = 350) (41)



(N = 58 SD = 0354 R2 = 0840 F = 945) (42)

wwwintechopencom



(43)


(44)



(N = 148 SD = 0192 R2 = 0985 F = 18561) (45)

wwwintechopencom



(N = 44 SD = 0167 R2 = 0978 F = 3442) (46)




N

Y

1086420

40

30

20

10

0

wwwintechopencom



N

Y

1086420

30

25

20

15

10

5

0




(N = 643 SD = 0357 R2 = 0992 F = 60830)

(47)


wwwintechopencom



(48)



Total Outliers














Total 720 77


7 References



wwwintechopencom


















wwwintechopencom


















wwwintechopencom


















wwwintechopencom
















wwwintechopencom


















wwwintechopencom

















wwwintechopencom

















wwwintechopencom
















wwwintechopencom











wwwintechopencom





Phone +86-21-62489820 Fax +86-21-62489821






(N = 47 SD = 0312 R2 = 0901 F = 450) (36)





N

Lo

g (

1N

PT

)

1086420

-1

-2

-3

-4

-5

wwwintechopencom




(N = 37 SD = 0320 R2 = 0951 F = 1559) (37)


(N = 54 SD = 0338 R2 = 0924 F = 14969) (38)


(N = 91 SD = 0433 R2 = 0936 F = 2045) (39)


wwwintechopencom



(N = 39 SD = 0103 R2 = 0980) (40)


(N = 45 SD = 0140 R2 = 0962 F = 350) (41)



(N = 58 SD = 0354 R2 = 0840 F = 945) (42)

wwwintechopencom



(43)


(44)



(N = 148 SD = 0192 R2 = 0985 F = 18561) (45)

wwwintechopencom



(N = 44 SD = 0167 R2 = 0978 F = 3442) (46)




N

Y

1086420

40

30

20

10

0

wwwintechopencom



N

Y

1086420

30

25

20

15

10

5

0




(N = 643 SD = 0357 R2 = 0992 F = 60830)

(47)


wwwintechopencom



(48)



Total Outliers














Total 720 77


7 References



wwwintechopencom


















wwwintechopencom


















wwwintechopencom


















wwwintechopencom
















wwwintechopencom


















wwwintechopencom

















wwwintechopencom

















wwwintechopencom
















wwwintechopencom











wwwintechopencom





Phone +86-21-62489820 Fax +86-21-62489821







(N = 37 SD = 0320 R2 = 0951 F = 1559) (37)


(N = 54 SD = 0338 R2 = 0924 F = 14969) (38)


(N = 91 SD = 0433 R2 = 0936 F = 2045) (39)


wwwintechopencom



(N = 39 SD = 0103 R2 = 0980) (40)


(N = 45 SD = 0140 R2 = 0962 F = 350) (41)



(N = 58 SD = 0354 R2 = 0840 F = 945) (42)

wwwintechopencom



(43)


(44)



(N = 148 SD = 0192 R2 = 0985 F = 18561) (45)

wwwintechopencom



(N = 44 SD = 0167 R2 = 0978 F = 3442) (46)




N

Y

1086420

40

30

20

10

0

wwwintechopencom



N

Y

1086420

30

25

20

15

10

5

0




(N = 643 SD = 0357 R2 = 0992 F = 60830)

(47)


wwwintechopencom



(48)



Total Outliers














Total 720 77


7 References



wwwintechopencom


















wwwintechopencom


















wwwintechopencom


















wwwintechopencom
















wwwintechopencom


















wwwintechopencom

















wwwintechopencom

















wwwintechopencom
















wwwintechopencom











wwwintechopencom





Phone +86-21-62489820 Fax +86-21-62489821






(N = 39 SD = 0103 R2 = 0980) (40)


(N = 45 SD = 0140 R2 = 0962 F = 350) (41)



(N = 58 SD = 0354 R2 = 0840 F = 945) (42)

wwwintechopencom



(43)


(44)



(N = 148 SD = 0192 R2 = 0985 F = 18561) (45)

wwwintechopencom



(N = 44 SD = 0167 R2 = 0978 F = 3442) (46)




N

Y

1086420

40

30

20

10

0

wwwintechopencom



N

Y

1086420

30

25

20

15

10

5

0




(N = 643 SD = 0357 R2 = 0992 F = 60830)

(47)


wwwintechopencom



(48)



Total Outliers














Total 720 77


7 References



wwwintechopencom


















wwwintechopencom


















wwwintechopencom


















wwwintechopencom
















wwwintechopencom


















wwwintechopencom

















wwwintechopencom

















wwwintechopencom
















wwwintechopencom











wwwintechopencom





Phone +86-21-62489820 Fax +86-21-62489821






(43)


(44)



(N = 148 SD = 0192 R2 = 0985 F = 18561) (45)

wwwintechopencom



(N = 44 SD = 0167 R2 = 0978 F = 3442) (46)




N

Y

1086420

40

30

20

10

0

wwwintechopencom



N

Y

1086420

30

25

20

15

10

5

0




(N = 643 SD = 0357 R2 = 0992 F = 60830)

(47)


wwwintechopencom



(48)



Total Outliers














Total 720 77


7 References



wwwintechopencom


















wwwintechopencom


















wwwintechopencom


















wwwintechopencom
















wwwintechopencom


















wwwintechopencom

















wwwintechopencom

















wwwintechopencom
















wwwintechopencom











wwwintechopencom





Phone +86-21-62489820 Fax +86-21-62489821






(N = 44 SD = 0167 R2 = 0978 F = 3442) (46)




N

Y

1086420

40

30

20

10

0

wwwintechopencom



N

Y

1086420

30

25

20

15

10

5

0




(N = 643 SD = 0357 R2 = 0992 F = 60830)

(47)


wwwintechopencom



(48)



Total Outliers














Total 720 77


7 References



wwwintechopencom


















wwwintechopencom


















wwwintechopencom


















wwwintechopencom
















wwwintechopencom


















wwwintechopencom

















wwwintechopencom

















wwwintechopencom
















wwwintechopencom











wwwintechopencom





Phone +86-21-62489820 Fax +86-21-62489821






N

Y

1086420

30

25

20

15

10

5

0




(N = 643 SD = 0357 R2 = 0992 F = 60830)

(47)


wwwintechopencom



(48)



Total Outliers














Total 720 77


7 References



wwwintechopencom


















wwwintechopencom


















wwwintechopencom


















wwwintechopencom
















wwwintechopencom


















wwwintechopencom

















wwwintechopencom

















wwwintechopencom
















wwwintechopencom











wwwintechopencom





Phone +86-21-62489820 Fax +86-21-62489821






(48)



Total Outliers














Total 720 77


7 References



wwwintechopencom


















wwwintechopencom


















wwwintechopencom


















wwwintechopencom
















wwwintechopencom


















wwwintechopencom

















wwwintechopencom

















wwwintechopencom
















wwwintechopencom











wwwintechopencom





Phone +86-21-62489820 Fax +86-21-62489821





















wwwintechopencom


















wwwintechopencom


















wwwintechopencom
















wwwintechopencom


















wwwintechopencom

















wwwintechopencom

















wwwintechopencom
















wwwintechopencom











wwwintechopencom





Phone +86-21-62489820 Fax +86-21-62489821





















wwwintechopencom


















wwwintechopencom
















wwwintechopencom


















wwwintechopencom

















wwwintechopencom

















wwwintechopencom
















wwwintechopencom











wwwintechopencom





Phone +86-21-62489820 Fax +86-21-62489821





















wwwintechopencom
















wwwintechopencom


















wwwintechopencom

















wwwintechopencom

















wwwintechopencom
















wwwintechopencom











wwwintechopencom





Phone +86-21-62489820 Fax +86-21-62489821



















wwwintechopencom


















wwwintechopencom

















wwwintechopencom

















wwwintechopencom
















wwwintechopencom











wwwintechopencom





Phone +86-21-62489820 Fax +86-21-62489821





















wwwintechopencom

















wwwintechopencom

















wwwintechopencom
















wwwintechopencom











wwwintechopencom





Phone +86-21-62489820 Fax +86-21-62489821




















wwwintechopencom

















wwwintechopencom
















wwwintechopencom











wwwintechopencom





Phone +86-21-62489820 Fax +86-21-62489821




















wwwintechopencom
















wwwintechopencom











wwwintechopencom





Phone +86-21-62489820 Fax +86-21-62489821



















wwwintechopencom











wwwintechopencom





Phone +86-21-62489820 Fax +86-21-62489821














wwwintechopencom





Phone +86-21-62489820 Fax +86-21-62489821








Phone +86-21-62489820 Fax +86-21-62489821




prediction of toxicity, sensory responses and biological .../67531/metadc155623/m2/1/high_re… ·...

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